HBase is an open source, distributed, column-oriented database modeled after Google's Bigtable that runs on top of Hadoop. The presenter discusses HBase's architecture, performance improvements in version 0.20 including major gains from new file formats and compression, and Stumbleupon's extensive use of HBase including supporting over 9 billion rows in a single table with high import and read speeds.
Real-time, Exactly-once Data Ingestion from Kafka to ClickHouse at eBayAltinity Ltd
LIVE WEBINAR: October 21, 2021 | 10 am PT
SPEAKERS: Jun Li, Principal Architect, eBay & Robert Hodges, CEO, Altinity
eBay depends on Kafka to solve the impedance mismatch between rapidly arriving messages in event streams and efficient block insert into ClickHouse clusters. Naïve loading procedures from Kafka to ClickHouse generate non-deterministic blocks, which can lead to data loss and incorrect results in applications. The eBay team solved this problem with a block aggregator that leverages Kafka to store message processing metadata as well as ClickHouse deduplication to ensure blocks being loaded to ClickHouse exactly once. The block aggregator allows eBay to support a sharded ClickHouse architecture across multiple data centers that can tolerate failures in any individual part of the system. Join us to learn how eBay developed this unique architecture and how they use it to deliver low-latency analytics to users.
Kafka on ZFS: Better Living Through Filesystems confluent
(Hugh O'Brien, Jet.com) Kafka Summit SF 2018
You’re doing disk IO wrong, let ZFS show you the way. ZFS on Linux is now stable. Say goodbye to JBOD, to directories in your reassignment plans, to unevenly used disks. Instead, have 8K Cloud IOPS for $25, SSD speed reads on spinning disks, in-kernel LZ4 compression and the smartest page cache on the planet. (Fear compactions no more!)
Learn how Jet’s Kafka clusters squeeze every drop of disk performance out of Azure, all completely transparent to Kafka.
-Striping cheap disks to maximize instance IOPS
-Block compression to reduce disk usage by ~80% (JSON data)
-Instance SSD as the secondary read cache (storing compressed data), eliminating >99% of disk reads and safe across host redeployments
-Upcoming features: Compressed blocks in memory, potentially quadrupling your page cache (RAM) for free
We’ll cover:
-Basic Principles
-Adapting ZFS for cloud instances (gotchas)
-Performance tuning for Kafka
-Benchmarks
HBaseCon 2015: OpenTSDB and AsyncHBase UpdateHBaseCon
OpenTSDB continues to scale along with HBase. A number of updates have been implemented to push writes over 2 million data points a second. Here we will discuss about HBase schema improvements, including salting, random UI assignment, and using append operations instead of puts. You'll also get AsyncHBase development updates about rate limiting, statistics, and security.
- Understanding Time Series
- What's the Fundamental Problem
- Prometheus Solution (v1.x)
- New Design of Prometheus (v2.x)
- Data Compression Algorithm
Replication, Durability, and Disaster RecoverySteven Francia
This session introduces the basic components of high availability before going into a deep dive on MongoDB replication. We'll explore some of the advanced capabilities with MongoDB replication and best practices to ensure data durability and redundancy. We'll also look at various deployment scenarios and disaster recovery configurations.
Speakers: Liang Xie and Honghua Feng (Xiamoi)
This talk covers the HBase environment at Xiaomi, including thoughts and practices around latency, hardware/OS/VM configuration, GC tuning, the use of a new write thread model and reverse scan, and block index optimization. It will also include some discussion of planned JIRAs based on these approaches.
Real-time, Exactly-once Data Ingestion from Kafka to ClickHouse at eBayAltinity Ltd
LIVE WEBINAR: October 21, 2021 | 10 am PT
SPEAKERS: Jun Li, Principal Architect, eBay & Robert Hodges, CEO, Altinity
eBay depends on Kafka to solve the impedance mismatch between rapidly arriving messages in event streams and efficient block insert into ClickHouse clusters. Naïve loading procedures from Kafka to ClickHouse generate non-deterministic blocks, which can lead to data loss and incorrect results in applications. The eBay team solved this problem with a block aggregator that leverages Kafka to store message processing metadata as well as ClickHouse deduplication to ensure blocks being loaded to ClickHouse exactly once. The block aggregator allows eBay to support a sharded ClickHouse architecture across multiple data centers that can tolerate failures in any individual part of the system. Join us to learn how eBay developed this unique architecture and how they use it to deliver low-latency analytics to users.
Kafka on ZFS: Better Living Through Filesystems confluent
(Hugh O'Brien, Jet.com) Kafka Summit SF 2018
You’re doing disk IO wrong, let ZFS show you the way. ZFS on Linux is now stable. Say goodbye to JBOD, to directories in your reassignment plans, to unevenly used disks. Instead, have 8K Cloud IOPS for $25, SSD speed reads on spinning disks, in-kernel LZ4 compression and the smartest page cache on the planet. (Fear compactions no more!)
Learn how Jet’s Kafka clusters squeeze every drop of disk performance out of Azure, all completely transparent to Kafka.
-Striping cheap disks to maximize instance IOPS
-Block compression to reduce disk usage by ~80% (JSON data)
-Instance SSD as the secondary read cache (storing compressed data), eliminating >99% of disk reads and safe across host redeployments
-Upcoming features: Compressed blocks in memory, potentially quadrupling your page cache (RAM) for free
We’ll cover:
-Basic Principles
-Adapting ZFS for cloud instances (gotchas)
-Performance tuning for Kafka
-Benchmarks
HBaseCon 2015: OpenTSDB and AsyncHBase UpdateHBaseCon
OpenTSDB continues to scale along with HBase. A number of updates have been implemented to push writes over 2 million data points a second. Here we will discuss about HBase schema improvements, including salting, random UI assignment, and using append operations instead of puts. You'll also get AsyncHBase development updates about rate limiting, statistics, and security.
- Understanding Time Series
- What's the Fundamental Problem
- Prometheus Solution (v1.x)
- New Design of Prometheus (v2.x)
- Data Compression Algorithm
Replication, Durability, and Disaster RecoverySteven Francia
This session introduces the basic components of high availability before going into a deep dive on MongoDB replication. We'll explore some of the advanced capabilities with MongoDB replication and best practices to ensure data durability and redundancy. We'll also look at various deployment scenarios and disaster recovery configurations.
Speakers: Liang Xie and Honghua Feng (Xiamoi)
This talk covers the HBase environment at Xiaomi, including thoughts and practices around latency, hardware/OS/VM configuration, GC tuning, the use of a new write thread model and reverse scan, and block index optimization. It will also include some discussion of planned JIRAs based on these approaches.
HBaseCon2017 Improving HBase availability in a multi tenant environmentHBaseCon
Infrastructure failures are a given in the cloud, but in a multi-tenant environment separating those failures from usage can be a challenge. I'll be presenting data gathered from over a hundred region server failures at HubSpot along with what we've done to improve our MTTR and what we're contributing back to the community. Covered topics will include separating usage-related failures from infrastructure and hardware failures, as well as steps we've taken to improve MTTR in both scenarios.
With employees based in countries around the globe which provide 24x7 services to MySQL users worldwide, Percona provides enterprise-grade MySQL Support, Consulting, Training, Managed Services, and Server Development services to companies ranging from large organizations, such as Cisco Systems, Alcatel-Lucent, Groupon, and the BBC, to recent startups building MySQL-powered solutions for businesses and consumers.
HBaseCon 2015: Blackbird Collections - In-situ Stream Processing in HBaseHBaseCon
Blackbird is a large-scale object store built at Rocket Fuel, which stores 100+ TB of data and provides real time access to 10 billion+ objects in a 2-3 milliseconds at a rate of 1 million+ times per second. In this talk (an update from HBaseCon 2014), we will describe Blackbird's comprehensive collections API and various examples of how it can be used to model collections like sets, maps, and aggregates on these collections like counters, etc. We will also illustrate the flexibility and power of the API by modeling custom collection types that are unique to the Rocket Fuel context.
PostgreSQL is designed to be easily extensible. For this reason, extensions loaded into the database can function just like features that are built in. In this session, we will learn more about PostgreSQL extension framework, how are they built, look at some popular extensions, management of these extensions in your deployments.
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBaseHBaseCon
In this presentation, we will introduce Hotspot's Garbage First collector (G1GC) as the most suitable collector for latency-sensitive applications running with large memory environments. We will first discuss G1GC internal operations and tuning opportunities, and also cover tuning flags that set desired GC pause targets, change adaptive GC thresholds, and adjust GC activities at runtime. We will provide several HBase case studies using Java heaps as large as 100GB that show how to best tune applications to remove unpredicted, protracted GC pauses.
Postgres & Redis Sitting in a Tree- Rimas Silkaitis, HerokuRedis Labs
Postgres and Redis Sitting in a Tree | In today’s world of polyglot persistence, it’s likely that companies will be using multiple data stores for storing and working with data based on the use case. Typically a company will
start with a relational database like Postgres and then add Redis for more high velocity use-cases. What if you could tie the two systems together to enable so much more?
HBase 2.0 is the next stable major release for Apache HBase scheduled for early 2017. It is the biggest and most exciting milestone release from the Apache community after 1.0. HBase-2.0 contains a large number of features that is long time in the development, some of which include rewritten region assignment, perf improvements (RPC, rewritten write pipeline, etc), async clients, C++ client, offheaping memstore and other buffers, Spark integration, shading of dependencies as well as a lot of other fixes and stability improvements. We will go into technical details on some of the most important improvements in the release, as well as what are the implications for the users in terms of API and upgrade paths. Existing users of HBase/Phoenix as well as operators managing HBase clusters will benefit the most where they can learn about the new release and the long list of features. We will also briefly cover earlier 1.x release lines and compatibility and upgrade paths for existing users and conclude by giving an outlook on the next level of initiatives for the project.
HBaseCon2017 Removable singularity: a story of HBase upgrade in PinterestHBaseCon
HBase is used to serve online facing traffic in Pinterest. It means no downtime is allowed. However, we were on HBase 94. To upgrade to latest version, we need to figure out a way to live upgrade while keeping Pinterest site live. Recently, we successfully upgrade 94 HBase cluster to 1.2 with no downtime. We made change to both Asynchbase and HBase server side. We will talk about what we did and how we did it. We will also talk about the finding in config and performance tuning we did to achieve low latency.
PostgreSQL Replication High Availability MethodsMydbops
This slides illustrates the need for replication in PostgreSQL, why do you need a replication DB topology, terminologies, replication nodes and many more.
HBaseCon2017 Improving HBase availability in a multi tenant environmentHBaseCon
Infrastructure failures are a given in the cloud, but in a multi-tenant environment separating those failures from usage can be a challenge. I'll be presenting data gathered from over a hundred region server failures at HubSpot along with what we've done to improve our MTTR and what we're contributing back to the community. Covered topics will include separating usage-related failures from infrastructure and hardware failures, as well as steps we've taken to improve MTTR in both scenarios.
With employees based in countries around the globe which provide 24x7 services to MySQL users worldwide, Percona provides enterprise-grade MySQL Support, Consulting, Training, Managed Services, and Server Development services to companies ranging from large organizations, such as Cisco Systems, Alcatel-Lucent, Groupon, and the BBC, to recent startups building MySQL-powered solutions for businesses and consumers.
HBaseCon 2015: Blackbird Collections - In-situ Stream Processing in HBaseHBaseCon
Blackbird is a large-scale object store built at Rocket Fuel, which stores 100+ TB of data and provides real time access to 10 billion+ objects in a 2-3 milliseconds at a rate of 1 million+ times per second. In this talk (an update from HBaseCon 2014), we will describe Blackbird's comprehensive collections API and various examples of how it can be used to model collections like sets, maps, and aggregates on these collections like counters, etc. We will also illustrate the flexibility and power of the API by modeling custom collection types that are unique to the Rocket Fuel context.
PostgreSQL is designed to be easily extensible. For this reason, extensions loaded into the database can function just like features that are built in. In this session, we will learn more about PostgreSQL extension framework, how are they built, look at some popular extensions, management of these extensions in your deployments.
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBaseHBaseCon
In this presentation, we will introduce Hotspot's Garbage First collector (G1GC) as the most suitable collector for latency-sensitive applications running with large memory environments. We will first discuss G1GC internal operations and tuning opportunities, and also cover tuning flags that set desired GC pause targets, change adaptive GC thresholds, and adjust GC activities at runtime. We will provide several HBase case studies using Java heaps as large as 100GB that show how to best tune applications to remove unpredicted, protracted GC pauses.
Postgres & Redis Sitting in a Tree- Rimas Silkaitis, HerokuRedis Labs
Postgres and Redis Sitting in a Tree | In today’s world of polyglot persistence, it’s likely that companies will be using multiple data stores for storing and working with data based on the use case. Typically a company will
start with a relational database like Postgres and then add Redis for more high velocity use-cases. What if you could tie the two systems together to enable so much more?
HBase 2.0 is the next stable major release for Apache HBase scheduled for early 2017. It is the biggest and most exciting milestone release from the Apache community after 1.0. HBase-2.0 contains a large number of features that is long time in the development, some of which include rewritten region assignment, perf improvements (RPC, rewritten write pipeline, etc), async clients, C++ client, offheaping memstore and other buffers, Spark integration, shading of dependencies as well as a lot of other fixes and stability improvements. We will go into technical details on some of the most important improvements in the release, as well as what are the implications for the users in terms of API and upgrade paths. Existing users of HBase/Phoenix as well as operators managing HBase clusters will benefit the most where they can learn about the new release and the long list of features. We will also briefly cover earlier 1.x release lines and compatibility and upgrade paths for existing users and conclude by giving an outlook on the next level of initiatives for the project.
HBaseCon2017 Removable singularity: a story of HBase upgrade in PinterestHBaseCon
HBase is used to serve online facing traffic in Pinterest. It means no downtime is allowed. However, we were on HBase 94. To upgrade to latest version, we need to figure out a way to live upgrade while keeping Pinterest site live. Recently, we successfully upgrade 94 HBase cluster to 1.2 with no downtime. We made change to both Asynchbase and HBase server side. We will talk about what we did and how we did it. We will also talk about the finding in config and performance tuning we did to achieve low latency.
PostgreSQL Replication High Availability MethodsMydbops
This slides illustrates the need for replication in PostgreSQL, why do you need a replication DB topology, terminologies, replication nodes and many more.
What Should I Do? Choosing SQL, NoSQL or Both for Scalable Web ApplicationsTodd Hoff
This is the slidedeck I used for a webinar (http://voltdb.com/choosing-sql-nosql-or-both-scalable-web-apps-webinar) I gave on helping people choose SQL or NoSQL for building scalabile web applications. Hint, the answer is: both.
Hadoop Summit 2012 | HBase Consistency and Performance ImprovementsCloudera, Inc.
The latest Apache HBase releases, 0.92 and 0.94, contain many improvements over prior releases in terms of correctness and performance improvements. We discuss a couple of these improvements from a development and operations perspective. For correctness, we discuss the ACID guarantees of HBase, give a case study of problems with earlier releases, and give an overview of the implementation internals that were improved to fix the issues. For performance, we discuss recent improvements in 0.94 and how to monitor the performance of a cluster with new metrics.
Sept 17 2013 - THUG - HBase a Technical IntroductionAdam Muise
HBase Technical Introduction. This deck includes a description of memory design, write path, read path, some operational tidbits, SQL on HBase (Phoenix and Hive), as well as HOYA (HBase on YARN).
Hadoop World 2011: Advanced HBase Schema DesignCloudera, Inc.
While running a simple key/value based solution on HBase usually requires an equally simple schema, it is less trivial to operate a different application that has to insert thousands of records per second.
This talk will address the architectural challenges when designing for either read or write performance imposed by HBase. It will include examples of real world use-cases and how they can be implemented on top of HBase, using schemas that optimize for the given access patterns.
Vladimir Rodionov (Hortonworks)
Time-series applications (sensor data, application/system logging events, user interactions etc) present a new set of data storage challenges: very high velocity and very high volume of data. This talk will present the recent development in Apache HBase that make it a good fit for time-series applications.
Hortonworks Technical Workshop: HBase For Mission Critical ApplicationsHortonworks
HBase adoption continues to explode amid rapid customer success and unbridled innovation. HBase with its limitless scalability, high reliability and deep integration with Hadoop ecosystem tools, offers enterprise developers a rich platform on which to build their next generation applications. In this workshop we will explore HBase SQL capabilities, deep Hadoop ecosystem integrations and deployment & management best practices.
With the public confession of Facebook, HBase is on everyone's lips when it comes to the discussion around the new "NoSQL" area of databases. In this talk, Lars will introduce and present a comprehensive overview of HBase. This includes the history of HBase, the underlying architecture, available interfaces, and integration with Hadoop.
Apache HBase™ is the Hadoop database, a distributed, salable, big data store.Its a column-oriented database management system that runs on top of HDFS.
Apache HBase is an open source NoSQL database that provides real-time read/write access to those large data sets. ... HBase is natively integrated with Hadoop and works seamlessly alongside other data access engines through YARN.
PostgreSQL is a well-known relational database. But in the last few years, it has gained capabilities that previously belonged only to "NoSQL" databases. In this talk, I describe several of PostgreSQL that give it such capabilities.
HBase hast established itself as the backend for many operational and interactive use-cases, powering well-known services that support millions of users and thousands of concurrent requests. In terms of features HBase has come a long way, overing advanced options such as multi-level caching on- and off-heap, pluggable request handling, fast recovery options such as region replicas, table snapshots for data governance, tuneable write-ahead logging and so on. This talk is based on the research for the an upcoming second release of the speakers HBase book, correlated with the practical experience in medium to large HBase projects around the world. You will learn how to plan for HBase, starting with the selection of the matching use-cases, to determining the number of servers needed, leading into performance tuning options. There is no reason to be afraid of using HBase, but knowing its basic premises and technical choices will make using it much more successful. You will also learn about many of the new features of HBase up to version 1.3, and where they are applicable.
From: DataWorks Summit 2017 - Munich - 20170406
HBase hast established itself as the backend for many operational and interactive use-cases, powering well-known services that support millions of users and thousands of concurrent requests. In terms of features HBase has come a long way, overing advanced options such as multi-level caching on- and off-heap, pluggable request handling, fast recovery options such as region replicas, table snapshots for data governance, tuneable write-ahead logging and so on. This talk is based on the research for the an upcoming second release of the speakers HBase book, correlated with the practical experience in medium to large HBase projects around the world. You will learn how to plan for HBase, starting with the selection of the matching use-cases, to determining the number of servers needed, leading into performance tuning options. There is no reason to be afraid of using HBase, but knowing its basic premises and technical choices will make using it much more successful. You will also learn about many of the new features of HBase up to version 1.3, and where they are applicable.
Solr cloud the 'search first' nosql database extended deep divelucenerevolution
Presented by Mark Miller, Software Engineer, Cloudera
As the NoSQL ecosystem looks to integrate great search, great search is naturally beginning to expose many NoSQL features. Will these Goliath's collide? Or will they remain specialized while intermingling – two sides of the same coin.
Come learn about where SolrCloud fits into the NoSQL landscape. What can it do? What will it do? And how will the big data, NoSQL, Search ecosystem evolve. If you are interested in Big Data, NoSQL, distributed systems, CAP theorem and other hype filled terms, than this talk may be for you.
The next major version - 0.96- of Apache HBase have several new features. The "Singularity", because you will have to start and stop your cluster to upgrade to 0.96. 0.96 requires Apache Hadoop 1.0.0 at least, and supported on Hadoop 2.0.0 as well. 0.96 uses protobufs all the time. All of its serializations to ZooKeeper, to the filesystem, and over rpc are protobufs. It runs on JDK7. Metrics have been edited and converted to use Hadoop Metrics2. It has HBase Snapshots and PrefixTreeCompression, etc. This presentation captures a high-level overview of what's new in HBase 0.96.
Flipboard services over 100 million users using heterogenous results including user generated content, interest profile, algorithmically generated content, social firehose, friends graph, ads, and web/rss crawlers. To personalize and serve these results in real time, Flipboard employs a variety of data models, access patterns and configuration. This talk will present how some of these strategies are implemented using HBase.
Speaker: Varun Sharma (Pinterest)
Over the past year, HBase has become an integral component of Pinterest's storage stack. HBase has enabled us to quickly launch and iterate on new products and create amazing pinner experiences. This talk briefly describes some of these applications, the underlying schema, and how our HBase setup stays highly available and performant despite billions of requests every week. It will also include some performance tips for running on SSDs. Finally, we will talk about a homegrown serving technology we built from a mashup of HBase components that has gained wide adoption across Pinterest.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
3. Now
• Personally rewri8en large porRons of HBase
for 0.20
– Code easy to work with, understand, modify
• Recently voted to commi8er status (thanks!)
• Now giving presentaRons (hi!)
NOSQL Meetup
4. Four Point Agenda
• What is HBase?
• Why HBase?
• HBase 0.20
• HBase At Stumbleupon
NOSQL Meetup
5. What is HBase?
• Clone of Bigtable ‐
h8p://labs.google.com/papers/bigtable.html
• Created originally at Powerset in 2007
• Hadoop‐subproject
– The usual ASF things apply (license, JIRA, etc)
NOSQL Meetup
7. Table & Regions
• Rows stored in byte‐lexographic sorted order
• Table dynamically split into “regions”
• Each region contains values [startKey, endKey)
• Regions hosted on a regionserver
NOSQL Meetup
11. Column Families
• Table consists of 1+ “column families”
• Column family is unit of performance tuning
• Stored in separate set of files
• Column names scoped like so:
– “Family:qualifier”
NOSQL Meetup
12. SorCng
• Rows stored in byte‐lexographical order (row
keys are raw bytes, not just strings)
• Furthermore within a row, columns stored in
sorted order
• Fast, cheap easy to scan adjacent rows &
columns
NOSQL Meetup
13. SorCng (but there’s more!)
• Not just scanning, but can do parRal‐key
lookups
• When combined with compound keys, has the
same properRes as leading‐lel edge indexes
in standard RDBMS
– (Except your index is distributed of course)
• Can use a second table to index a primary
table.
NOSQL Meetup
16. API Example
Scan scan = new Scan(startRow,
endRow).addFamily(“family”);
ResultScanner scanner = table.getScanner(scan);
Result result;
while ( (result=scanner.next()) != null) {
EnRty e = new EnRty();
dser.deserialize(e, result.getValue("default”, “0”);
}
scanner.close();
NOSQL Meetup
17. Why HBase?
• Community is highly acRve, diverse, helpful
• User list Email acRvity for May: 78 threads
• IRC Channel #hbase highly acRve
• Helpful people in mulRple Rmezones, email
answered all hours of the day/night/weekend.
NOSQL Meetup
18. Why HBase?
• Commi8er & contributor base broad:
– PSet, Streamy, SU, Trend Micro, Openplaces, and
more!
• No monopoly on experts – deep knowledge at
these companies and more!
• (We’re really friendly… honest!)
NOSQL Meetup
24. HBase 0.20 vs 0.19
0.19 0.20
Master Single master – if it fails, so Master elecRon and
does the cluster membership via ZK
Compression Not really GZ, LZO
Memory usage Small values cause big New file‐format limits
indexes and OOM index size (800kB for 10m
entries)
Scan Speed 300‐600ms per 500 rows 20‐30ms per 500 rows
NOSQL Meetup
27. Performance
• Significant performance gains in 0.20
• New file format with 0‐copy infrastructure
• Scan and get improvements
• LZO compression
• Block caching
• Speed increases as much as 30x!
NOSQL Meetup
29. Performance Numbers
• 1m rows, 1 column per row (~16 bytes)
– SequenRal insert: 24s, .024ms/row
– Random read: 1.42ms/row (avg)
– Full Scan: 11s, (117ms/10k rows)
• Performance under cache is very high:
– 1ms to get single row
– 20 ms to read 550 rows
– 75ms to get 5500 rows
NOSQL Meetup
31. Big accomplishments @ SU
• Over 9b small rows in single table
– Sustained import performance – 3‐4 days to
import 9b rows (mysql limiRng speed)
• 1.2m row reads/sec on 19 nodes (!!)
– That is 60‐100k reads/sec/node sustained, 2hrs
– Scalable with more nodes
– HBase has been improved since then
NOSQL Meetup
34. HBase deployment trivia
• Nodes are 8x16 w/2TB (best price point)
– Don’t use RAID1. Use RAID0 or JBOD support
• Ganglia allows overall cluster performance
monitoring
• Clusters won’t span datacenters
– We want fully duplicate data for DR anyways
• Update master with code & config
– Rsync to other nodes (1 dir, very easy)
– Controlled restart for rolling upgrade
NOSQL Meetup
35. HBase deployment trivia
• HDFS – set xciever limit to 2048, Xmx2000m
– Never get HDFS problems even under heavy load
• For 9b row import, randomized key insert order
gives substanRal speedup
• Give HBase enough ram, you wouldn’t starve
mysql!
• Import speeds of 200k ops/sec on 19 machines
possible!
– Hard to provide a SQL‐based source fast enough
– 100k ops/sec typical for sustained
NOSQL Meetup
37. HBase future @ SU
• Latency sensiRve cluster
• Batch/analyRcs cluster
• Use replicaRon to keep la8er up to date
• Allows batch jobs to go full thro8le against
reasonably up to date data without risking the
website
NOSQL Meetup