What we Learned About Application Resiliency When the Data Center Burned Down

•

0 likes•164 views

Is your data infrastructure architected to withstand anything —including a disaster suddenly taking down an entire data center? When a cloud provider’s data center burned to the ground, 3.6 million websites went dark. But one leading travel service kept running without a hitch, thanks to the design of their environment-aware distributed database. Learn how they architected their data infrastructure for extreme resiliency, how their strategy held up and what lessons they learned.

Technology

What Can Be Learned
About Application Resiliency
When Your Datacenter Burns Down?
Lessons from a real-world disaster

Peter Corless
+ Listen to customer stories
+ Write blogs & case studies
+ Play (and design) strategy &
roleplaying games
Technical Marketing Manager
ScyllaDB

10 March 2021, 0:47 AM — Disaster Strikes
SBG2 datacenter of OVHcloud
was entirely destroyed by ﬁre

What would do if your datacenter
was on ﬁre?

Massive, Systemic Disaster
...as if millions of alarms triggered at once and were suddenly silenced

OVHcloud Fire
OVHcloud’s Strasbourg SBG2 Datacenter engulfed
in ﬂames.
(Image: SDIS du Bas Rhin)

About Kiwi.com
➔ Virtual global supercarrier
➔ Seamless travel experience
➔ Connecting “A” to “B”
➔ Virtual interlining

8
A Database Built for High Availability
Latencies brieﬂy rise
until unavailable servers
are taken out of cluster
10 of 30 servers
are suddenly
unavailable
Requests per
second per server;
note how some
drop towards zero
then blip out of
existence

Geographically Distributed Datacenters
>500km
>250km
>550km

OVHcloud’s Strasbourg SBG2 Datacenter
the next morning. (Image via Twitter)
➔ Strasbourg datacenter impact
■ SBG2 totally consumed
■ SBG1 4 of 12 rooms gutted
■ SBG3 & SBG4 proactively taken oﬄine
➔ Internet impact (as per Netcraft)
■ 3.6 million websites
■ 464,000 domains
■ 1 in 50 sites in all of .fr TLD
Datacenter Damage Assessment

Kiwi.com’s Timeline of Fire
00:47 CET Fire breaks out in OVHcloud Strasbourg SBG2
01:12 CET Kiwi.com nodes in Strasbourg start falling off the cluster
01:15 CET All 10 Strasbourg nodes oﬄine; traﬃc diverted to 2x other Kiwi.com datacenters (20
servers remaining)
02:23 CET Production operational, we manually need to tweak some services around the main
database.
08:54 CET Tweaks deployed, we are fully operational

ScyllaDB
15
+ Reimagined the distributed NoSQL database
+ Close-to-the-hardware design, written in C++
+ Open source, enterprise & DBaaS
+ From the creators of KVM hypervisor
Winner Infoworld
Technology
of the Year

17
Used across industries
AdTech/MarTech
Multimedia Finance/FinTech Security
Ride-hailing/
Food Delivery
Social Retail Travel IoT Logistics/Transportation

– Consistency Options –
Eventual consistency
to linearizability
– Presences –
1 to 10+ datacenter
replications
– Volume –
Multi-petabyte
– Throughput –
1 billion OPS
18
– Vertical Scalability –
1 to 416 vCPUs
– Horizontal Scalability –
1,000-node cluster
– Availability –
1 to 10+ replicas
within a datacenter
– Unlimited –
Cell sizes and
partition width
Grows with your business & your data
Learn more ▸ scylladb.com

+ Architect for disaster from the start
+ Eliminate any and all single points of failure (SPOFs = bad)
+ Datacenter-aware topology & distribution; multi-datacenter replication
+ Consider suﬃcient excess capacity in case a whole datacenter goes down
+ Consider contingency plans for multicloud architectures or alternate standby
sites [and standby hardware]
+ Do regular chaos monkey work
Lessons Learned

+ Consider running a “torpedo test” during Proof of Concepts & scalability testing
+ Take down a node, then another, then another…
+ How long does it take for a cluster to rebalance after losing a node?
+ How much of a latency/throughput hit do you take after losing a node?
+ After how many “torpedoes” does your system just “sink?” [Go non-linear]
+ How long does it take for a single node to be restored?
+ After taking n torpedoes, long does a system take to restore back to full
operations?
Consider “Torpedo Testing”

United States
2445 Faber St, Suite #200
Palo Alto, CA USA 94303
Israel
Maskit 4
Herzliya, Israel 4673304
www.scylladb.com
@scylladb
Learn NoSQL for free!
university.scylladb.com
@petercorless

This document discusses the attributes of a high-performance, low-latency database like ScyllaDB. It begins with introductions and an overview of ScyllaDB. It then summarizes how hardware has evolved over 20 years with more cores, memory, and faster disks. ScyllaDB was redesigned from first principles to take advantage of modern hardware, using an asynchronous, shared-nothing architecture with one shard per core. This allows it to achieve significantly higher performance than Cassandra. The document shows benchmark results demonstrating ScyllaDB's lower latencies and ability to scale to higher throughput. It also discusses how ScyllaDB uses workload prioritization to manage different types of workloads.

Building modern data lakes

Minio

The Do’s and Don’ts of Benchmarking Databases

ScyllaDB

With so many moving parts, how can you be sure that a tweak to your database is really beneficial or just a measurement fluke? And how can you be sure that your benchmark is measuring the right thing? In this webinar you will learn a set of best practices to improve the quality of your benchmarks, including how to... Evaluate changes to database systems, whether you are a code contributor or a user playing with knobs Determine what to measure for the most accurate results Make benchmarks that are strong, solid, and reliable We will also cover how to judge whether benchmarks with incredible claims are to be trusted.

Introduction to Container Storage Interface (CSI)

Idan Atias

Among the cool stuff we do at Silk, my colleagues and I develop the Silk CSI Plugin for customers who use our system as the storage layer for their Kubernetes workloads. Before deep diving into the code and as part of my ramp-up on this subject I prepared some slides that cover some basic and important information on this topic. These slides start by recapping some basic storage principals in containers and Kubernetes, continues with some more advanced use cases (including an "offline demo" of persisting Redis data on EBS volumes), and ends with a detailed information on the CSI solution itself. IMHO, reviewing these slides can improve your understanding on this matter and can get you started implementing your own CSI plugin. The main sources of information I used for preparing these slides are: * Official CSI docs * Kubernetes Storage Lingo 101 - Saad Ali, Google * Container Storage Interface: Present and Future - Jie Yu, Mesosphere, Inc.

Steering the Sea Monster - Integrating Scylla with Kubernetes

ScyllaDB

Kubernetes is a declarative system for automatically deploying, managing, and scaling server-side applications and their dependencies. In this webinar, we will introduce Kubernetes at a high level and demonstrate how to get started using Scylla with Kubernetes and Google Compute Engine. Join us to: Understand the principles of Kubernetes and how it solves common problems of deploying distributed applications Explore an example configuration of Scylla with Kubernetes that can serve as a starting point for your own system. Get insight into the performance characteristics of Scylla when it it is run in a container (e.g. Docker) and deployed via Kubernetes.

Webinar how to build a highly available time series solution with kairos-db (1)

Julia Angell

NoSQL and NewSQL: Tradeoffs between Scalable Performance & Consistency

ScyllaDB

Jolt: Distributed, fault-tolerant test running at scale using Mesos

Mesosphere Inc.

This document summarizes Yelp's new test parallelization system called Jolt. It discusses how Jolt bundles tests into groups to run in parallel on Mesos clusters. This improves upon their previous system called Seagull which had complex custom components. Jolt uses Task Processing to interface with Mesos in a composable way. The document also describes Yelp's autoscaling system called Clusterman which adjusts Mesos cluster sizes based on resource usage and spot instance pricing. It notes how these systems have significantly reduced Yelp's infrastructure costs while improving their ability to run tests and deploy code.

Most databases are based on architectures that pre-date advances to modern hardware. This results in performance issues, the need to overprovision, and a high total cost of ownership. In this webinar we will discuss the advances to modern server technology and take a deep dive into Scylla’s shard-per-core architecture and our asynchronous engine, the Seastar framework. Join us to learn how Seastar (and Scylla): Avoid locks and contention on the CPU level Bypass kernel bottlenecks Implement its per-core shared-nothing autosharding mechanism Utilize modern storage hardware Leverage NUMA to get the best RAM performance Balance your data across CPUs and nodes for best and smoothest performance Plus we’ll cover the advantages of unlocking vertical scalability.

Scylla Virtual Workshop 2020

ScyllaDB

Learn how to get started with Scylla Join us for an overview of NoSQL best practices and get a look into the scale-out vs scale up models and the Scylla philosophy for accelerated success. In this session, we will show you how to get fast wins when using Scylla. We will cover architectural concepts, installation best practices, data model antipatterns, use case examples, scale-out vs. scale up approaches and management and monitoring tools. If you’re a database architect, developer, or manager, this session is for you! Architectural concepts Installation of a single cluster of Scylla Using Docker to get a 3-node cluster on your laptop Connecting your application to the database Data model antipatterns Management and monitoring installation

Big Data Day LA 2015 - Sparking up your Cassandra Cluster- Analytics made Awe...

Data Con LA

After a brief technical introduction to Apache Cassandra we'll then go into the exciting world of Apache Spark integration, and learn how you can turn your transactional datastore into an analytics platform. Apache Spark has taken the Hadoop world by storm (no pun intended!), and is widely seen as the replacement to Hadoop Map Reduce. Apache Spark coupled with Cassandra are perfect allies, Cassandra does the distributed data storage, Spark does the distributed computation.

Comparing Apache Cassandra 4.0, 3.0, and ScyllaDB

ScyllaDB

How does Cassandra 4.0’s performance compare to Cassandra 3.x’s? What’s been fixed in 4.0 and what remains unchanged? Should you upgrade or consider other options? Join us for a webinar where we’ll answer these questions and more, based on our extensive benchmarks comparing Cassandra 4.0 against Cassandra 3.11. We’ll also share how the new release of Cassandra stacks up against Scylla Open Source. You’ll learn the rationale and results for our head-to-head comparisons, including: - Throughput under various loads - Comparison of long-tail (p95, p99) latencies - Improvements to operations such as compactions If you are considering upgrading your existing infrastructure from Cassandra 3.11, or if you are considering a new wide column database for a greenfield deployment, this is a session you won’t want to miss!

TechTalk: Reduce Your Storage Footprint with a Revolutionary New Compaction S...

ScyllaDB

Compaction. A necessary reality in databases with immutable table designs. To date, Scylla and Cassandra compaction strategies for SSTables have had tradeoffs. For example, size-tiered compaction strategy requires leaving 50% of your total drive space unused in order to compact large tables. What if there was a new, better, more efficient way to handle compactions in Scylla? One that allows you to use your storage much more efficiently? Enter Scylla’s unique Incremental Compaction Strategy (ICS). Join us for a comparison of common compaction strategies and a technical deep dive into ICS. You’ll learn why ICS will become the new standard for compaction, including an overview of how much disk space you can save with ICS.

Overcoming Barriers of Scaling Your Database

ScyllaDB

Scaling distributed databases successfully requires meeting myriad challenges from physical distribution of your data across on-premises locations, public cloud vendors, geographies and political entities to adopting technologies to overcome fundamental operational bottlenecks. Join ScyllaDB's Peter Corless, director of technical advocacy, as he interviews Moreno Garcia y Silva, head of solution architecture, about how to navigate both technical ecosystem and database architectural challenges for this next tech cycle. Takeaways: - Recognizing and classifying barriers to scaling - Solutions to overcome scaling challenges - Upfront planning and real-time response

Introducing Scylla Open Source 4.0

ScyllaDB

Since its inception, Scylla has offered a compelling alternative to Apache Cassandra, providing better performance for a lower cost of ownership. With Scylla Open Source 4.0 we continue to extend our CQL interface features and capabilities and also now provide an open source alternative to DynamoDB, allowing you to run your workloads anywhere, on any cloud provider, or on premises. Join ScyllaDB co-founders, CTO Avi Kivity and CEO Dor Laor, for a look at the new features in Scylla Open Source 4.0, and architectural and cost comparisons with the coming Cassandra 4.0. Topics will include: Improved consistency with our new Lightweight Transactions Scylla Operator for Kubernetes How we stack up against Apache Cassandra 4.0 Our “run anywhere” DynamoDB alternative

Spark Powered by Scylla

ScyllaDB

Register to see webinar: http://go.scylladb.com/wbn-spark-scylla-registration.html Spark has become the de-facto analytics tool for data stored in Scylla. In this webinar we will review different workloads using Spark and Scylla, for example Extract, Transform, Load (ETL), creating joins between tables and summaries and reporting. We will also cover data modeling best practices for Scylla-Spark use cases and different deployment scenarios. To conclude, we will share performance tuning settings to utilize both Scylla and Spark at peak performance. Join us to learn... Why using Spark with Scylla is advantageous for analytics workloads How to create reporting using Spark and Scylla Best practices for data modeling and performance tuning for Scylla and Spark

How to achieve no compromise performance and availability

ScyllaDB

12.07.2017 Docker Meetup - POSTGRE SQL ON KUBERNETES

Zalando adtech lab

Dynamic Object Routing

Cloudian

Running a DynamoDB-compatible Database on Managed Kubernetes Services

ScyllaDB

With the release of Alternator, Scylla’s DynamoDB-compatible API, you can now take your locked-in DynamoDB workloads and run them anywhere. Scylla provides a cost-effective open source alternative to Amazon’s DynamoDB, deployable wherever a user would want: on-premises, on other public clouds like Microsoft Azure or Google Cloud Platform, still on AWS (such as the high-density i3en instances) or as a fully managed DBaaS. In this session, we will cover: - Scylla Alternator: Scylla’s Amazon DynamoDB-compatible API - Scylla Operator: Running Scylla Alternator on Kubernetes - Demo Alternator - Demo and explain DynamoDB on GKE

Big Data on Cloud Native Platform

Sunil Govindan

Measuring Database Performance on Bare Metal AWS Instances

ScyllaDB

AWS has recently announced a new type of instance targeted at I/O intensive applications, the i3.metal. That instance does away with the virtualization layer altogether and gives back the resources that would otherwise be used by the hypervisor back to the application. To use all of those resources — 72 CPUs and 512GB of memory — a database needs to be have the ability to scale both up and out. In this webinar we will look into the performance of Scylla running in a few of those instances versus Apache Cassandra running in their sweet spot, a larger fleet of smaller instances. We will discuss how much of the gains come from the database design and how much come from the removal of the virtualization layer. Key takeaways: How to properly compare two different database technologies while being fair to both How to choose the optimal setup for your Scylla deployment How AWS’s bare metal servers enable Scylla users to draw a significant performance boost.

Adam Dagnall: Advanced S3 compatible storage integration in CloudStack

ShapeBlue

Adam's slides from his talk at the CloudStack European User group meetup, March 13, London. To provide tighter integration between the S3 compatible object store and CloudStack, Cloudian has developed a connector to allow users and their applications to utilize the object store directly from within the CloudStack platform in a single sign-on manner with self-service provisioning. Additionally, CloudStack templates and snapshots are centrally stored within the object store and managed through the CloudStack service. The object store offers protection of these templates and snapshots across data centres using replication or erasure coding.

On CloudStack, Docker, Kubernetes, and Big Data…Oh my ! By Sebastien Goasguen...

Radhika Puthiyetath

Sebastien Goasguen is a developer who works on Apache CloudStack and other open source projects related to cloud computing, containers, and big data. He gave a talk covering CloudStack, Docker, Kubernetes, CoreOS, and how various technologies can work together for managing distributed applications and infrastructure. He also discussed the evolving landscape of cloud computing and how big data solutions fit within that landscape.

Database Jiu Jitsu: How ScyllaDB Open Sourced a DynamoDB-compatible API

ScyllaDB

Amazon has a well earned reputation for commercializing open source database software. Now emerging open source NoSQL challenger ScyllaDB has turned the tables by releasing an API that gives DynamoDB users an easy path to a highly performant alternative that’s much less expensive. ScyllaDB puts an end to vendor lockin. It lets you run on any cloud platform and deploy anywhere. You can run Scylla as a fully managed service (even on-prem) or open source. Join Corey Quinn, Chief Cloud Economist at the Duckbill Group, and ScyllaDB founder and CEO Dor Laor for an informative session on new options available to DynamoDB users. From attending this session you’ll learn: What people ask for vs. what they really want from their databases The challenges companies experience with DynamoDB How ScyllaDB frees DynamoDB users from vendor lockin AWS’s offerings and how ScyllaDB fits into this progression A comparison of performance and TCO

How to Build a Scylla Database Cluster that Fits Your Needs

ScyllaDB

Sizing a database cluster makes or breaks your application. Too small and you could sustain spikes in usage and recover from a node loss or an operational slowdown. Too big and your cluster will cost more and waste valuable human resources. Since different workloads have different requirements, successful sizing of your application should be optimized for both throughput and latency performance. However, in many cases, the requirements for each contradicts each other. In this webinar, we explain how to remediate the contradicting forces and build a sustainable cluster to meet both performance and resiliency requirements.

Numberly on Joining Billions of Rows in Seconds: Replacing MongoDB and Hive w...

ScyllaDB

Many organizations struggle to balance traditional big data infrastructure with NoSQL databases. Other organizations do the smart thing and consolidate the two. This presentation explores Numberly’s experience migrating an intensive and join-hungry production workload from MongoDB and Hive to Scylla. Join Alexys Jacob, CTO of Numberly, to learn how they joined billions of rows in seconds and dramatically reduced operational and development complexity by using a single database for their hybrid analytical use case. As a bonus, Alexys will also cover benchmarks for Dask (a flexible parallel computing library for analytic computing) and Spark, highlighting their differences and lessons learned along the way.

Introducing Cloudian HyperStore 6.0

Cloudian

Exploring Phantom Traffic Jams in Your Data Flows

ScyllaDB

This document discusses phantom traffic jams that can occur in data flows even without true hardware bottlenecks. It explains how producer-consumer systems with jitter at the producer, consumer, or dispatcher can lead to self-limiting behavior and effective dispatch rates below capacity. The document advocates for good metrics and analyzing bottlenecks with an interposer that can measure queue lengths rather than assuming hardware limitations. It provides a simulator experiment to demonstrate these effects and conclusions about checking bottlenecks throughout systems instead of only at hardware.

Dataline Tysons Corner 100808 Barry Lynn

GovCloud Network

3tera provides cloud computing services that allow information technology assets to be more private and secure in the cloud compared to traditional data centers. The cloud offers massive scalability on demand with computing, storage, and other services that users can access without knowledge of the underlying technology. This reduces capital expenditures by allowing resources to be shared and only paying for what is consumed. 3tera's cloud platform further reduces costs by handling hardware failures and providing a single management interface for resources, applications, and users. Cloud computing will continue to evolve and eventually all information technology, including legacy systems, web applications, and storage, will be hosted in the cloud, which will become the next great utility for IT.

What's hot

Under the Hood of a Shard-per-Core Database Architecture

ScyllaDB

Scylla Virtual Workshop 2020

ScyllaDB

Big Data Day LA 2015 - Sparking up your Cassandra Cluster- Analytics made Awe...

Data Con LA

Comparing Apache Cassandra 4.0, 3.0, and ScyllaDB

ScyllaDB

TechTalk: Reduce Your Storage Footprint with a Revolutionary New Compaction S...

ScyllaDB

Overcoming Barriers of Scaling Your Database

ScyllaDB

Introducing Scylla Open Source 4.0

ScyllaDB

Spark Powered by Scylla

ScyllaDB

How to achieve no compromise performance and availability

ScyllaDB

12.07.2017 Docker Meetup - POSTGRE SQL ON KUBERNETES

Zalando adtech lab

Dynamic Object Routing

Cloudian

Running a DynamoDB-compatible Database on Managed Kubernetes Services

ScyllaDB

Big Data on Cloud Native Platform

Sunil Govindan

Measuring Database Performance on Bare Metal AWS Instances

ScyllaDB

Adam Dagnall: Advanced S3 compatible storage integration in CloudStack

ShapeBlue

On CloudStack, Docker, Kubernetes, and Big Data…Oh my ! By Sebastien Goasguen...

Radhika Puthiyetath

Database Jiu Jitsu: How ScyllaDB Open Sourced a DynamoDB-compatible API

ScyllaDB

How to Build a Scylla Database Cluster that Fits Your Needs

ScyllaDB

Numberly on Joining Billions of Rows in Seconds: Replacing MongoDB and Hive w...

ScyllaDB

Introducing Cloudian HyperStore 6.0

Cloudian

What's hot (20)

Under the Hood of a Shard-per-Core Database Architecture

Scylla Virtual Workshop 2020

Big Data Day LA 2015 - Sparking up your Cassandra Cluster- Analytics made Awe...

Comparing Apache Cassandra 4.0, 3.0, and ScyllaDB

TechTalk: Reduce Your Storage Footprint with a Revolutionary New Compaction S...

Overcoming Barriers of Scaling Your Database

Introducing Scylla Open Source 4.0

Spark Powered by Scylla

How to achieve no compromise performance and availability

12.07.2017 Docker Meetup - POSTGRE SQL ON KUBERNETES

Dynamic Object Routing

Running a DynamoDB-compatible Database on Managed Kubernetes Services

Big Data on Cloud Native Platform

Measuring Database Performance on Bare Metal AWS Instances

Adam Dagnall: Advanced S3 compatible storage integration in CloudStack

On CloudStack, Docker, Kubernetes, and Big Data…Oh my ! By Sebastien Goasguen...

Database Jiu Jitsu: How ScyllaDB Open Sourced a DynamoDB-compatible API

How to Build a Scylla Database Cluster that Fits Your Needs

Numberly on Joining Billions of Rows in Seconds: Replacing MongoDB and Hive w...

Introducing Cloudian HyperStore 6.0

Similar to What we Learned About Application Resiliency When the Data Center Burned Down

Exploring Phantom Traffic Jams in Your Data Flows

ScyllaDB

Dataline Tysons Corner 100808 Barry Lynn

GovCloud Network

Techmeeting-17feb2016

Marko Broedersz

The document discusses IBM LinuxONE and ICU's strategy. It describes LinuxONE as IBM's portfolio of Linux systems, including the z13s, z13, Emperor, and Rockhopper models. It outlines ICU's plans to focus on simplifying infrastructure with virtualized systems, improved security and manageability, and combining stable backends with flexible frontends. ICU will facilitate expertise through a playground, proofs of concept, demos, benchmarking, and one touch deployment of demo infrastructures.

EGITF 2013 - Bringing Private Cloud Computing to HPC and Science with OpenNebula

OpenNebula Project

This presentation discusses bringing private cloud computing to HPC and science. It covers the private HPC cloud use case, main challenges, and case studies of private HPC clouds implemented at various research centers. Some key points discussed include using OpenNebula to provide infrastructure and provisioning tools for private clouds, addressing issues like application performance and resource management, and how grid and cloud computing can be complementary models.

Bringing Private Cloud computing to HPC and Science - EGI TF tf 2013

Ignacio M. Llorente

This document discusses bringing private cloud computing to high-performance computing (HPC) and science. It covers the private HPC cloud use case, main challenges, and case studies from several research centers that have implemented private HPC clouds using OpenNebula. Some key challenges discussed are flexible application definitions, resource management at scale, performance considerations, and hybrid cloud deployments. Private cloud trends from industry are also briefly summarized.

Citi Tech Talk: Hybrid Cloud

confluent

The Crown Jewels: Is Enterprise Data Ready for the Cloud?

Inside Analysis

The Briefing Room with Dr. Robin Bloor and NuoDB Live Webcast on March 25, 2014 Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=ac6cb15c0aaaa6d044784969e4187696 Enterprise organizations are already deeply embedded in the cloud, whether it’s via Salesforce.com for customer relationship management or Marketo for marketing and lead generation. But frequently the most significant impediment to moving the crown jewels of corporate data to the cloud is the database. A cloud database must be secure, flexible enough to solve a variety of problems, easy to automate and administer, and able to run in multiple cloud data centers simultaneously. Plus, it should be consistently resilient in the face of failure, not to mention cost-effective, just like the cloud itself. Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains how cloud deployments are the inevitable next step for information management. He will be joined by Jim Starkey, co-founder of NuoDB, who will discuss the common reasons enterprises shy away from leveraging a database in the cloud, as well as how next generation DBMS, purpose-built for the cloud, can create strategic organizational advantage. Visit InsideAnlaysis.com for more information.

Distributed Database Design Decisions to Support High Performance Event Strea...

StreamNative

Event streaming architectures launched a reexamination of applications and systems architectures across the board. We live in a world where answers are needed now in a constant real-time flow. Yet beyond the event streaming system itself, what are the corequisites to ensure our large scale distributed database systems can keep pace with this always-on, always-current real time flow of data? What are the requirements and expectations for this next tech cycle?

2014 01-23-eranea-apalia-private-cloud

Didier Durand

Learning Rust the Hard Way for a Production Kafka + ScyllaDB Pipeline

ScyllaDB

🎥 Sign up for upcoming webinars or browse through our library of on-demand recordings here: https://www.scylladb.com/resources/webinars/ About this webinar: Numberly operates business-critical data pipelines and applications where failure and latency means "lost money" in the best-case scenario. Most of their data pipelines and applications are deployed on Kubernetes and rely on Kafka and ScyllaDB, with Kafka acting as the message bus and ScyllaDB as the source of data for enrichment. The availability and latency of both systems are thus very important for data pipelines. While most of Numberly’s applications are developed using Python, they found a need to move high-performance applications to Rust in order to benefit from a lower-level programming language. Learn the lessons from Numberly’s experience, including: - Rationale in selecting a lower-level language - Developing using a lower-level Rust code base - Observability and analyzing latency impacts with Rust - Tuning everything from Apache Avro to driver client settings - How to build a mission-critical system combining Apache Kafka and ScyllaDB - Half a year Rust in production feedback

Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...

confluent

Lookout is a mobile cybersecurity company that ingests telemetry data from hundreds of millions of mobile devices to provide security scanning and apply corporate policies. They were facing scaling issues with their existing data pipeline and storage as the number of devices grew. They decided to use Apache Kafka and Confluent Platform for scalable data ingestion and ScyllaDB as the persistent store. Testing showed the new architecture could handle their target of 1 million devices with low latency and significantly lower costs compared to their previous DynamoDB-based solution. Key learnings included improving Kafka's default partitioner and working through issues during proof of concept testing with ScyllaDB.

Data Pipeline with Docker on AWS

Adeesh Fulay

We at Robin Systems help customers deploy data pipelines both on-premises and on the cloud. In this session, we will walk through different examples of data pipelines designed to cater to different data sets and use cases like Twitter feeds, IoT sensor data, recommendations, etc and their deployment using Docker containers. We will also discuss different considerations to simplify management of the data pipeline in terms of performance, availability, recoverability, scaling, etc Event: Santa Clara Docker Meetup

cncf overview and building edge computing using kubernetes

Krishna-Kumar

CisCon 2018 - SDN, complessità e TCO: non c’è un modo più semplice?

AreaNetworking.it

Relatore: Andrea Dainese, Network & Security Architect, speaker, advisor, Cisco CCIE #38620 E’ un dato di fatto che oggi le infrastrutture stanno diventando sempre più complesse e difficili da mantenere. Ed è ancora più difficile e costoso trovare risorse in grado di operare e far evolvere correttamente reti e datacenter. Vedremo assieme come e perchè siamo arrivati a dover introdurre tecnologie complesse, quali scelte abbiamo per approcciare consapevolemtne il problema e come sta evolvendo la professione del networker, in senso lato. Concluderemo con una panoramica sulle soluzioni disponibili nel mercato, focalizzandoci sulle peculiarità di Cisco ACI, in modo da poterla valutare e paragonare correttamente.

Ingestion in data pipelines with Managed Kafka Clusters in Azure HDInsight

Microsoft Tech Community

This document provides an overview of Apache Kafka on Azure HDInsight, including its key features such as 99.9% availability, support for various development tools, enterprise security features, integration with other Azure services, and examples of how it is used by customers for real-time analytics and streaming workloads. It also includes diagrams illustrating how Kafka works and call-outs about Kafka's scalability, fault tolerance, and pub-sub model.

Distributech_Presentation DTECH_2013

Dorian Hernandez

The document discusses Burlington Electric Department's deployment of a secure distributed SCADA (DSCADA) system using data-diodes in a self-contained fiber-optic network. It describes how the system shares data from a high security SCADA network to a lower security business LAN network through uni-directional gateways for improved isolation and security. The deployment addressed issues with the previous firewall-based system and provides benefits like complete isolation of the critical SCADA systems while still enabling necessary communications.

Docker Workshop

Alex Baretto

Docker allows applications to be packaged with all their dependencies and run consistently across any infrastructure. It creates lightweight containers that can be moved between environments like development, testing, and production without changes. This solves issues caused by different application component combinations and environments by standardizing the deployment package. Docker eliminates complexity through portable containers that can be easily built, shipped, and run anywhere.

OpenNebula Conf 2014 | From private cloud to laaS public services for Catalan...

NETWAYS

Nowadays, Catalan Academic and research institutions can enjoy self-service cloud infrastructure in order to meet their application needs in a flexible pay per use mode. An self-service platform is available for managing servers, networks and assigned storage from the Universities Consortium Data Centers, allowing users access to a customizable infrastructure with an orientation towards the so-call virtual DC.

OpenNebulaConf 2014 - From private cloud to laaS public services for Catalan ...

OpenNebula Project

This document summarizes a presentation about moving a Catalan research and education community from a private cloud to public infrastructure as a service (IaaS) clouds. The presentation discusses the evolution of the community's data center services from dedicated servers to virtual data centers and hybrid solutions using OpenNebula. It provides details on the new OpenNebula 4.8 installation including host configuration, networking, storage, and software ecosystem. The presentation addresses some myths about cloudification including the relevance of the hypervisor and whether clouds need to always be on or can be hybrid. It concludes that the community now has IaaS services in their hands and should promote OpenNebula usage.

Demystifying the Distributed Database Landscape (DevOps) (1).pdf

ScyllaDB

What is the state of high-performance, distributed databases as we head deeper into 2022, and which options are best suited for your own development projects? The data-intensive applications leading this next tech cycle are typically powered by multiple types of databases and data stores—each satisfying specific needs and often interacting with a broader data ecosystem. Even the very notion of a database is evolving as new hardware architectures and methodologies allow for ever-greater capabilities and expectations for horizontal and vertical scalability, performance and reliability. In this webinar, Peter Corless, ScyllaDB’s director of technology advocacy, will survey the current landscape of distributed database systems and highlight new directions in the industry. This talk will cover different database and database-adjacent technologies as well as describe their appropriate use cases, patterns and anti-patterns with a focus on: - Distributed SQL, NewSQL and NoSQL - In-memory datastores and caches - Streaming technologies with persistent data storage

Similar to What we Learned About Application Resiliency When the Data Center Burned Down (20)

Exploring Phantom Traffic Jams in Your Data Flows

Dataline Tysons Corner 100808 Barry Lynn

Techmeeting-17feb2016

EGITF 2013 - Bringing Private Cloud Computing to HPC and Science with OpenNebula

Bringing Private Cloud computing to HPC and Science - EGI TF tf 2013

Citi Tech Talk: Hybrid Cloud

The Crown Jewels: Is Enterprise Data Ready for the Cloud?

Distributed Database Design Decisions to Support High Performance Event Strea...

2014 01-23-eranea-apalia-private-cloud

Learning Rust the Hard Way for a Production Kafka + ScyllaDB Pipeline

Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...

Data Pipeline with Docker on AWS

cncf overview and building edge computing using kubernetes

CisCon 2018 - SDN, complessità e TCO: non c’è un modo più semplice?

Ingestion in data pipelines with Managed Kafka Clusters in Azure HDInsight

Distributech_Presentation DTECH_2013

Docker Workshop

OpenNebula Conf 2014 | From private cloud to laaS public services for Catalan...

OpenNebulaConf 2014 - From private cloud to laaS public services for Catalan ...

Demystifying the Distributed Database Landscape (DevOps) (1).pdf

More from ScyllaDB

Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency

ScyllaDB

Optimizing NoSQL Performance Through Observability

ScyllaDB

ScyllaDB has the potential to deliver impressive performance and scalability. The better you understand how it works, the more you can squeeze out of it. But before you squeeze, make sure you know what to monitor! Watch our experienced Postgres developer work through monitoring and performance strategies that help him understand what mistakes he’s made moving to NoSQL. And learn with him as our database performance expert offers friendly guidance on how to use monitoring and performance tuning to get his sample Rust application on the right track. This webinar focuses on using monitoring and performance tuning to discover and correct mistakes that commonly occur when developers move from SQL to NoSQL. For example: - Common issues getting up and running with the monitoring stack - Using the CQL optimizations dashboard - Common issues causing high latency in a node - Common issues causing replica imbalance - What a healthy system looks like in terms of memory - Key metrics to keep an eye on This isn’t “Death-by-Powerpoint.” We’ll walk through problems encountered while migrating a real application from Postgres to ScyllaDB – and try to fix them live as well.

Event-Driven Architecture Masterclass: Challenges in Stream Processing

ScyllaDB

Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...

ScyllaDB

Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...

ScyllaDB

Developer Data Modeling Mistakes: From Postgres to NoSQL

ScyllaDB

See where an RDBMS-pro’s intuition leads him astray – and learn practical tips for the data modeling transition ScyllaDB has the potential to deliver impressive performance and scalability. The better you understand how it works, the more you can squeeze out of it. However, developers new to high-performance NoSQL intuitively shoot themselves in the foot with respect to things like table design, query design, indexing, and partitioning. Watch where our experienced Postgres developer intuitively falls into traps that hurt performance and scalability. And learn with him as our database performance expert offers friendly guidance on navigating all the unexpected behaviors that tend to trip up RDBMS experts. This webinar focuses on common data modeling and querying mistakes that occur when developers move from SQL to NoSQL. For example: - Understanding query first design principles - Planning for schema evolution - Steering clear of common pitfalls and anti-patterns - Assessing data access patterns This isn’t “Death-by-Powerpoint.” We’ll walk through problems encountered while migrating a real application from Postgres to ScyllaDB – and try to fix them live as well.

What Developers Need to Unlearn for High Performance NoSQL

ScyllaDB

See where an RDBMS-pro’s intuition leads him astray – and learn practical tips for the transition ScyllaDB has the potential to deliver impressive performance and scalability. The better you understand how it works, the more you can squeeze out of it. However, developers new to high-performance NoSQL intuitively shoot themselves in the foot with respect to things like table design, query design, indexing, and partitioning. Watch where our experienced Postgres developer intuitively falls into traps that hurt performance and scalability. And learn with him as our database performance expert offers friendly guidance on navigating all the unexpected behaviors that tend to trip up RDBMS experts. Our first webinar of this series will cover common mistakes with practices such as: - Translating the data model to NoSQL - Optimizing table design - Optimizing query performance - Planning for partitioning This isn’t “Death-by-Powerpoint.” We’ll walk through problems encountered while migrating a real application from Postgres to ScyllaDB – and try to fix them live as well.

Low Latency at Extreme Scale: Proven Practices & Pitfalls

ScyllaDB

Expert tips on how to maximize your database performance at scale Untangle the complexity of achieving database performance at scale. Join this webinar to discover commonly overlooked ways to get predictable low latency, even at extreme scale. Our Solution Architects will walk you through the strategies and pitfalls learned by working on thousands of real-world distributed database projects, many reaching 1M OPS with single-digit MS latencies. In addition to offering clear recommendations, we’ll also explain the process behind how we arrived at them – so you can benefit from the lessons learned by other teams. We’ll cover how to: - Design and deploy a large-scale distributed database cluster - Optimize your clients’ interactions with it - Expand the cluster horizontally and globally - Ensure it survives whatever disasters the world throws at it

Dissecting Real-World Database Performance Dilemmas

ScyllaDB

Tackling your own database performance challenges is serious business. For a change of pace, let’s have some fun learning from other teams’ performance predicaments. Join us for an interactive session where we dissect four specific database performance challenges faced by teams considering or using ScyllaDB. For each dilemma, we'll: - Examine the context and technical requirements - Talk about potential solutions and cover the pros and cons of each - Disclose what approach the team took, and how it worked out About the speaker: Felipe is an IT specialist with years of experience on distributed systems and open-source technologies. He is one of the co-authors of "Database Performance at Scale", an Open Access, freely available publication for individuals interested on improving database performance. At ScyllaDB, he works as a Solution Architect.

Beyond Linear Scaling: A New Path for Performance with ScyllaDB

ScyllaDB

Linear scaling (sometimes near linear scaling) is often mentioned in several benchmarks, articles and product comparisons as proof that a given technology and algorithmic optimizations perform better than another. But is that really what performance is all about, and should you even care? This webinar discusses performance beyond linear scalability, including what typically matters more when running high throughput and low latency workloads at scale. We'll cover how ScyllaDB offers unparalleled performance and share our insights on: - The hidden aspects of linear scaling - When linear scaling matters most and when it’s simply irrelevant - Often overlooked considerations for optimizing and measuring distributed systems performance Watch now to learn from our experience (and lessons learned) in building the fastest NoSQL database in the world.

Dissecting Real-World Database Performance Dilemmas

ScyllaDB

Navigating Complex Database Performance Hurdles Tackling your own database performance challenges is serious business. For a change of pace, let’s have some fun learning from other teams’ performance predicaments. Join us for an interactive session where we dissect 4 specific database performance challenges faced by teams considering or using ScyllaDB. For each dilemma: - The presenters will describe the context and technical requirements - Together, we’ll talk about potential solutions and cover the pros and cons of each - Finally, we’ll disclose what approach the team took, and how it worked out Throughout the event, we’ll have opportunities to win ScyllaDB swag and prizes! Come prepared to engage in lively discussions and gain valuable insight into database performance strategies.

Database Performance at Scale Masterclass: Workload Characteristics by Felipe...

ScyllaDB

Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...

ScyllaDB

Database Performance at Scale Masterclass: Driver Strategies by Piotr Sarna

ScyllaDB

Replacing Your Cache with ScyllaDB

ScyllaDB

This document discusses replacing external caching solutions with using the internal caching capabilities of ScyllaDB. It provides examples of companies that improved performance, reduced costs and complexity by moving from Redis or Elasticsearch with an external cache to using ScyllaDB's embedded cache instead. The document also outlines some of the advantages of ScyllaDB's cache like improved latency, coherency with the database and observability compared to external caching layers.

Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability

ScyllaDB

Discover how your team can achieve low latency at the extreme scale that your data-intensive applications require. We’ll walk you through an example of how ScyllaDB scales linearly to achieve 1M and then 2M OPS – with <1ms P99 latency. We’ll cover how this works on a sample realtime app (an ML feature store), share best practices for performance, and talk about the most important tradeoffs you’ll need to negotiate. Join us to learn: - Why and how to ensure your database takes full advantage of your cloud infrastructure - What architectural considerations matter most for high throughput and low latency - Key factors to consider when selecting a high-performance database

7 Reasons Not to Put an External Cache in Front of Your Database.pptx

ScyllaDB

This document discusses the pros and cons of placing an external cache in front of a database. It introduces Tomasz Grabiec and Tzach Livyatan from ScyllaDB and describes ScyllaDB's optimized internal caching design. External caches can increase latency and costs while ignoring the database's context and workload knowledge. ScyllaDB embeds its cache to minimize overhead and ensure data and query awareness. The document shares customer examples that improved performance and reduced costs by moving from cached databases to ScyllaDB.

Getting the most out of ScyllaDB

ScyllaDB

Expert tips on how to maximize your database potential If you’re considering or getting started with ScyllaDB, you’re probably intrigued by its potential to achieve high throughput and predictable low latency at a reasonable cost. So how do you ensure that you’re maximizing that potential for your team’s specific workloads and use case? This webinar offers practical advice for navigating the various decision points you’ll face as you assess whether ScyllaDB is a good fit for your team and later roll it out into production. We’ll cover the most critical considerations, tradeoffs, and recommendations related to: - Infrastructure selection - ScyllaDB configuration - Client-side setup - Data modeling

NoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration

ScyllaDB

NoSQL Database Migration Masterclass - Session 3: Migration Logistics

ScyllaDB

More from ScyllaDB (20)

Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency

Optimizing NoSQL Performance Through Observability

Event-Driven Architecture Masterclass: Challenges in Stream Processing

Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...

Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...

Developer Data Modeling Mistakes: From Postgres to NoSQL

What Developers Need to Unlearn for High Performance NoSQL

Low Latency at Extreme Scale: Proven Practices & Pitfalls

Dissecting Real-World Database Performance Dilemmas

Beyond Linear Scaling: A New Path for Performance with ScyllaDB

Dissecting Real-World Database Performance Dilemmas

Database Performance at Scale Masterclass: Workload Characteristics by Felipe...

Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...

Database Performance at Scale Masterclass: Driver Strategies by Piotr Sarna

Replacing Your Cache with ScyllaDB

Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability

7 Reasons Not to Put an External Cache in Front of Your Database.pptx

Getting the most out of ScyllaDB

NoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration

NoSQL Database Migration Masterclass - Session 3: Migration Logistics

Recently uploaded

UiPath Test Automation using UiPath Test Suite series, part 6

DianaGray10

Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI. UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities. Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes. What will you get from this session? 1. Insights into integrating generative AI. 2. Understanding how this integration enhances test automation within the UiPath platform 3. Practical demonstrations 4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath Topics covered: What is generative AI Test Automation with generative AI and Open AI. UiPath integration with generative AI Speaker: Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP

OpenID AuthZEN Interop Read Out - Authorization

David Brossard

National Security Agency - NSA mobile device best practices

Quotidiano Piemontese

20240607 QFM018 Elixir Reading List May 2024

Matthew Sinclair

Your One-Stop Shop for Python Success: Top 10 US Python Development Providers

akankshawande

AI 101: An Introduction to the Basics and Impact of Artificial Intelligence

IndexBug

Fueling AI with Great Data with Airbyte Webinar

Zilliz

みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...

名前です男

Cosa hanno in comune un mattoncino Lego e la backdoor XZ?

Speck&Tech

ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune. Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile. BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).

Uni Systems Copilot event_05062024_C.Vlachos.pdf

Uni Systems S.M.S.A.

Ocean lotus Threat actors project by John Sitima 2024 (1).pptx

SitimaJohn

Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.

Mind map of terminologies used in context of Generative AI

Kumud Singh

Choosing The Best AWS Service For Your Website + API.pptx

Brandon Minnick, MBA

Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API? Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose? Which one is cheapest? Which one is fastest? Which one will scale to meet our needs? Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!

Building Production Ready Search Pipelines with Spark and Milvus

Zilliz

Mariano G Tinti - Decoding SpaceX

Mariano Tinti

Presentation of the OECD Artificial Intelligence Review of Germany

innovationoecd

HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU

panagenda

Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/ DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen! Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell. Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten. Diese Themen werden behandelt - Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten - Wie funktionieren CCB- und CCX-Lizenzen wirklich? - Verstehen des DLAU-Tools und wie man es am besten nutzt - Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw. - Praxisbeispiele und Best Practices zum sofortigen Umsetzen

UI5 Controls simplified - UI5con2024 presentation

Wouter Lemaire

Artificial Intelligence for XMLDevelopment

Octavian Nadolu

In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject. We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup. Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved. The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring. The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise. By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.

Microsoft - Power Platform_G.Aspiotis.pdf

Uni Systems S.M.S.A.

Recently uploaded (20)

UiPath Test Automation using UiPath Test Suite series, part 6

OpenID AuthZEN Interop Read Out - Authorization

National Security Agency - NSA mobile device best practices

20240607 QFM018 Elixir Reading List May 2024

Your One-Stop Shop for Python Success: Top 10 US Python Development Providers

AI 101: An Introduction to the Basics and Impact of Artificial Intelligence

Fueling AI with Great Data with Airbyte Webinar

Cosa hanno in comune un mattoncino Lego e la backdoor XZ?

Uni Systems Copilot event_05062024_C.Vlachos.pdf

Ocean lotus Threat actors project by John Sitima 2024 (1).pptx

Mind map of terminologies used in context of Generative AI

Choosing The Best AWS Service For Your Website + API.pptx

Building Production Ready Search Pipelines with Spark and Milvus

Mariano G Tinti - Decoding SpaceX

Presentation of the OECD Artificial Intelligence Review of Germany

HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU

UI5 Controls simplified - UI5con2024 presentation

Artificial Intelligence for XMLDevelopment

Microsoft - Power Platform_G.Aspiotis.pdf

What we Learned About Application Resiliency When the Data Center Burned Down

1. What Can Be Learned About Application Resiliency When Your Datacenter Burns Down? Lessons from a real-world disaster

2. Peter Corless + Listen to customer stories + Write blogs & case studies + Play (and design) strategy & roleplaying games Technical Marketing Manager ScyllaDB

3. 10 March 2021, 0:47 AM — Disaster Strikes SBG2 datacenter of OVHcloud was entirely destroyed by ﬁre

4. What would do if your datacenter was on ﬁre?

5. Massive, Systemic Disaster ...as if millions of alarms triggered at once and were suddenly silenced

6. OVHcloud Fire OVHcloud’s Strasbourg SBG2 Datacenter engulfed in ﬂames. (Image: SDIS du Bas Rhin)

7. About Kiwi.com ➔ Virtual global supercarrier ➔ Seamless travel experience ➔ Connecting “A” to “B” ➔ Virtual interlining

8. 8 A Database Built for High Availability Latencies brieﬂy rise until unavailable servers are taken out of cluster 10 of 30 servers are suddenly unavailable Requests per second per server; note how some drop towards zero then blip out of existence

9. “This is a non-stop ﬂight…”

10. Geographically Distributed Datacenters >500km >250km >550km

11. Main database locations

12. OVHcloud’s Strasbourg SBG2 Datacenter the next morning. (Image via Twitter) ➔ Strasbourg datacenter impact ■ SBG2 totally consumed ■ SBG1 4 of 12 rooms gutted ■ SBG3 & SBG4 proactively taken oﬄine ➔ Internet impact (as per Netcraft) ■ 3.6 million websites ■ 464,000 domains ■ 1 in 50 sites in all of .fr TLD Datacenter Damage Assessment

13. Kiwi.com’s Timeline of Fire 00:47 CET Fire breaks out in OVHcloud Strasbourg SBG2 01:12 CET Kiwi.com nodes in Strasbourg start falling off the cluster 01:15 CET All 10 Strasbourg nodes oﬄine; traﬃc diverted to 2x other Kiwi.com datacenters (20 servers remaining) 02:23 CET Production operational, we manually need to tweak some services around the main database. 08:54 CET Tweaks deployed, we are fully operational

14. Basically...

15. ScyllaDB 15 + Reimagined the distributed NoSQL database + Close-to-the-hardware design, written in C++ + Open source, enterprise & DBaaS + From the creators of KVM hypervisor Winner Infoworld Technology of the Year

16.

17. 17 Used across industries AdTech/MarTech Multimedia Finance/FinTech Security Ride-hailing/ Food Delivery Social Retail Travel IoT Logistics/Transportation

18. – Consistency Options – Eventual consistency to linearizability – Presences – 1 to 10+ datacenter replications – Volume – Multi-petabyte – Throughput – 1 billion OPS 18 – Vertical Scalability – 1 to 416 vCPUs – Horizontal Scalability – 1,000-node cluster – Availability – 1 to 10+ replicas within a datacenter – Unlimited – Cell sizes and partition width Grows with your business & your data Learn more ▸ scylladb.com

19. + Architect for disaster from the start + Eliminate any and all single points of failure (SPOFs = bad) + Datacenter-aware topology & distribution; multi-datacenter replication + Consider suﬃcient excess capacity in case a whole datacenter goes down + Consider contingency plans for multicloud architectures or alternate standby sites [and standby hardware] + Do regular chaos monkey work Lessons Learned

20. + Consider running a “torpedo test” during Proof of Concepts & scalability testing + Take down a node, then another, then another… + How long does it take for a cluster to rebalance after losing a node? + How much of a latency/throughput hit do you take after losing a node? + After how many “torpedoes” does your system just “sink?” [Go non-linear] + How long does it take for a single node to be restored? + After taking n torpedoes, long does a system take to restore back to full operations? Consider “Torpedo Testing”

21. A New Hope [For DevOps]

22. United States 2445 Faber St, Suite #200 Palo Alto, CA USA 94303 Israel Maskit 4 Herzliya, Israel 4673304 www.scylladb.com @scylladb Learn NoSQL for free! university.scylladb.com @petercorless

What we Learned About Application Resiliency When the Data Center Burned Down

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to What we Learned About Application Resiliency When the Data Center Burned Down

Similar to What we Learned About Application Resiliency When the Data Center Burned Down (20)

More from ScyllaDB

More from ScyllaDB (20)

Recently uploaded

Recently uploaded (20)

What we Learned About Application Resiliency When the Data Center Burned Down