Datadog is a cloud monitoring solution that brings metrics from all of your apps, tools, servers & services into one place. It brings servers, clouds, metrics, apps, and team together by seamlessly aggregating metrics and events across the full devops stack.
The ability to monitor infrastructure and application performance in real time is essential to every software organization. Now, with the MongoDB Atlas and Datadog integration, you can seamlessly track Atlas performance monitoring data in Datadog. You can use Datadog to correlate performance metrics and events across your entire stack, create custom graphs and dashboards, as well as setup advanced alerting to help identify issues.
Datadog: From a single product to a growing platform by Alexis Lê-Quôc, CTOTheFamily
By Alexis (https://twitter.com/alq), CTO at Datadog (https://www.datadoghq.com)
Alexis built Datadog's whole infrastructure and team from scratch as a co-founder. From a very small & dedicated team with no experience, he learned step by step to build a complete product ️
He shared with us his experience as a co-founder and CTO building a cloud giant in New York. How do you keep learning, how do you interact with customers & your market to drive your product development, and how do you monitor it all to make you company evolve will be the main topics of his talk.
Datadog is a cloud monitoring solution that brings metrics from all of your apps, tools, servers & services into one place. It brings servers, clouds, metrics, apps, and team together by seamlessly aggregating metrics and events across the full devops stack.
The ability to monitor infrastructure and application performance in real time is essential to every software organization. Now, with the MongoDB Atlas and Datadog integration, you can seamlessly track Atlas performance monitoring data in Datadog. You can use Datadog to correlate performance metrics and events across your entire stack, create custom graphs and dashboards, as well as setup advanced alerting to help identify issues.
Datadog: From a single product to a growing platform by Alexis Lê-Quôc, CTOTheFamily
By Alexis (https://twitter.com/alq), CTO at Datadog (https://www.datadoghq.com)
Alexis built Datadog's whole infrastructure and team from scratch as a co-founder. From a very small & dedicated team with no experience, he learned step by step to build a complete product ️
He shared with us his experience as a co-founder and CTO building a cloud giant in New York. How do you keep learning, how do you interact with customers & your market to drive your product development, and how do you monitor it all to make you company evolve will be the main topics of his talk.
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
Cisco and AppDynamics: Redefining Application Intelligence - AppD Summit EuropeAppDynamics
On the 20th March 2017, AppDynamics was acquired by Cisco for $3.7B, the biggest M&A multiple for a company bought for over $1B. This acquisition reinforces Cisco’s strategic direction, shifting to software-centric solutions and analytics. AppDynamics’ real-time data platform will be correlated with Cisco’s data platforms over time, giving joint customers the richest end-to-end view (from business to user to app to infrastructure), allowing for better remediation and automation.
In this session, come and hear what’s next, as Tejaswi Redkar, Head of Products and Experience in the Cloud and Analytics Business Unit at Cisco and Adam Leftik, VP of Product Management, at AppDynamics, go deeper into the value Cisco and AppDynamics will bring. Tejaswi and Adam will detail:
- The announcement and its significance for the software and infrastructure industries
- How the acquisition will redefine application intelligence
For more information, visit: www.appdynamics.com
Is your company built on software? How do you know if your customer's experience is slow and sucks? How do you debug slowness or troubleshoot an incident? Observability! David Mitchell, VP of Engineering at Datadog will talk to use about Observability, why it's important, what it is and how Datadog helps reduce toil in your environment.
GDG Cloud Southlake #13
Observability has emerged as one of the hottest topics on the DevOps landscape. Organizations seek to improve visibility into their cloud infrastructure and applications and identify production issues that may negatively impact #customerexperience.
➡️ But what are some of the best practices for scaling observability for modernapplications?
➡️ What challenges are #cloudplatforms facing?
Explore how to overcome the challenges and unlock speed, observability, and automation across your DevOps lifecycle.
PyData NYC 2015 - Automatically Detecting Outliers with Datadog Datadog
Monitoring even a modestly-sized systems infrastructure quickly becomes untenable without automated alerting. For many metrics it is nontrivial to define ahead of time what constitutes “normal” versus “abnormal” values. This is especially true for metrics whose baseline value fluctuates over time. To make this problem more tractable, Datadog provides outlier detection functionality to automatically identify any host (or group of hosts) that is behaving abnormally compared to its peers.
These slides cover the algorithms we use for outlier detection, and show how easy they are to implement using Python. This presentation also covers the lessons we've learned from using outlier detection on our own systems, along with some real-life examples on how to avoid false positives and negatives.
Learn more at www.datadoghq.com.
Customer case - Dynatrace Monitoring RedefinedMichel Duruel
One of the largest Airline in the world chose Dynatrace, here is the customer case.
Including:
Vision and Goal / Challenges / Requirements / Why Dynatrace is Unique / ROI and TCO / Rollout Status / Solution Screenshots
Dynatrace redefined monitoring with AI powered 3rd Generation APM, User Experience Monitoring & Continuous Improvement, Cloud-native, Full Stack, Auto Everything, End-to-End, Easiest to Implement, Use and Maintain
Whoops, The Numbers Are Wrong! Scaling Data Quality @ NetflixDataWorks Summit
Netflix is a famously data-driven company. Data is used to make informed decisions on everything from content acquisition to content delivery, and everything in-between. As with any data-driven company, it’s critical that data used by the business is accurate. Or, at worst, that the business has visibility into potential quality issues as soon as they arise. But even in the most mature data warehouses, data quality can be hard. How can we ensure high quality in a cloud-based, internet-scale, modern big data warehouse employing a variety of data engineering technologies?
In this talk, Michelle Ufford will share how the Data Engineering & Analytics team at Netflix is doing exactly that. We’ll kick things off with a quick overview of Netflix’s analytics environment, then dig into details of our data quality solution. We’ll cover what worked, what didn’t work so well, and what we plan to work on next. We’ll conclude with some tips and lessons learned for ensuring data quality on big data.
Improve monitoring and observability for kubernetes with oss toolsNilesh Gule
Slide deck from the ASEAN Cloud Summit meetup on 27 January 2022. The session cover the following topics
1 - Centralized Loggin with Elasticsearch, Fluentbit and Kibana
2 - Monitoring and Alerting with Prometheus and Grafana
3 - Exception aggregation with Sentry
The live demo showcased these aspects using Azure Kubernetes Service (AKS)
Observability in Java: Getting Started with OpenTelemetryDevOps.com
Our software is more complex than ever: applications must be reliable, predictable, and easy to use to meet modern expectations. As developers, this means our responsibilities have grown while the things we can control have stayed the same. In order to better understand our systems and create truly modern software, we need observability.
This workshop will walk through what observability means for Java developers and how to achieve it in our systems with the least amount of work using the open source observability project OpenTelemetry.
Application monitoring is being talked about a lot these days and it helps provide key information that is helpful in developing better software and also in taking some key business decision. Datadog offers monitoring as a service.
Lifting the Blinds: Monitoring Windows Server 2012Datadog
Operating systems monitor resources continuously in order to effectively schedule processes.
In this webinar, Evan Mouzakitis (Datadog) discusses how to get operational data from Windows Server 2012 using a variety of native tools.
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
Cisco and AppDynamics: Redefining Application Intelligence - AppD Summit EuropeAppDynamics
On the 20th March 2017, AppDynamics was acquired by Cisco for $3.7B, the biggest M&A multiple for a company bought for over $1B. This acquisition reinforces Cisco’s strategic direction, shifting to software-centric solutions and analytics. AppDynamics’ real-time data platform will be correlated with Cisco’s data platforms over time, giving joint customers the richest end-to-end view (from business to user to app to infrastructure), allowing for better remediation and automation.
In this session, come and hear what’s next, as Tejaswi Redkar, Head of Products and Experience in the Cloud and Analytics Business Unit at Cisco and Adam Leftik, VP of Product Management, at AppDynamics, go deeper into the value Cisco and AppDynamics will bring. Tejaswi and Adam will detail:
- The announcement and its significance for the software and infrastructure industries
- How the acquisition will redefine application intelligence
For more information, visit: www.appdynamics.com
Is your company built on software? How do you know if your customer's experience is slow and sucks? How do you debug slowness or troubleshoot an incident? Observability! David Mitchell, VP of Engineering at Datadog will talk to use about Observability, why it's important, what it is and how Datadog helps reduce toil in your environment.
GDG Cloud Southlake #13
Observability has emerged as one of the hottest topics on the DevOps landscape. Organizations seek to improve visibility into their cloud infrastructure and applications and identify production issues that may negatively impact #customerexperience.
➡️ But what are some of the best practices for scaling observability for modernapplications?
➡️ What challenges are #cloudplatforms facing?
Explore how to overcome the challenges and unlock speed, observability, and automation across your DevOps lifecycle.
PyData NYC 2015 - Automatically Detecting Outliers with Datadog Datadog
Monitoring even a modestly-sized systems infrastructure quickly becomes untenable without automated alerting. For many metrics it is nontrivial to define ahead of time what constitutes “normal” versus “abnormal” values. This is especially true for metrics whose baseline value fluctuates over time. To make this problem more tractable, Datadog provides outlier detection functionality to automatically identify any host (or group of hosts) that is behaving abnormally compared to its peers.
These slides cover the algorithms we use for outlier detection, and show how easy they are to implement using Python. This presentation also covers the lessons we've learned from using outlier detection on our own systems, along with some real-life examples on how to avoid false positives and negatives.
Learn more at www.datadoghq.com.
Customer case - Dynatrace Monitoring RedefinedMichel Duruel
One of the largest Airline in the world chose Dynatrace, here is the customer case.
Including:
Vision and Goal / Challenges / Requirements / Why Dynatrace is Unique / ROI and TCO / Rollout Status / Solution Screenshots
Dynatrace redefined monitoring with AI powered 3rd Generation APM, User Experience Monitoring & Continuous Improvement, Cloud-native, Full Stack, Auto Everything, End-to-End, Easiest to Implement, Use and Maintain
Whoops, The Numbers Are Wrong! Scaling Data Quality @ NetflixDataWorks Summit
Netflix is a famously data-driven company. Data is used to make informed decisions on everything from content acquisition to content delivery, and everything in-between. As with any data-driven company, it’s critical that data used by the business is accurate. Or, at worst, that the business has visibility into potential quality issues as soon as they arise. But even in the most mature data warehouses, data quality can be hard. How can we ensure high quality in a cloud-based, internet-scale, modern big data warehouse employing a variety of data engineering technologies?
In this talk, Michelle Ufford will share how the Data Engineering & Analytics team at Netflix is doing exactly that. We’ll kick things off with a quick overview of Netflix’s analytics environment, then dig into details of our data quality solution. We’ll cover what worked, what didn’t work so well, and what we plan to work on next. We’ll conclude with some tips and lessons learned for ensuring data quality on big data.
Improve monitoring and observability for kubernetes with oss toolsNilesh Gule
Slide deck from the ASEAN Cloud Summit meetup on 27 January 2022. The session cover the following topics
1 - Centralized Loggin with Elasticsearch, Fluentbit and Kibana
2 - Monitoring and Alerting with Prometheus and Grafana
3 - Exception aggregation with Sentry
The live demo showcased these aspects using Azure Kubernetes Service (AKS)
Observability in Java: Getting Started with OpenTelemetryDevOps.com
Our software is more complex than ever: applications must be reliable, predictable, and easy to use to meet modern expectations. As developers, this means our responsibilities have grown while the things we can control have stayed the same. In order to better understand our systems and create truly modern software, we need observability.
This workshop will walk through what observability means for Java developers and how to achieve it in our systems with the least amount of work using the open source observability project OpenTelemetry.
Application monitoring is being talked about a lot these days and it helps provide key information that is helpful in developing better software and also in taking some key business decision. Datadog offers monitoring as a service.
Lifting the Blinds: Monitoring Windows Server 2012Datadog
Operating systems monitor resources continuously in order to effectively schedule processes.
In this webinar, Evan Mouzakitis (Datadog) discusses how to get operational data from Windows Server 2012 using a variety of native tools.
Containerization (à la Docker) is increasing the elastic nature of cloud infrastructure by an order of magnitude. If you have adopted Docker, or are considering it, you are probably facing questions like:
- How many containers can you run on a given Amazon EC2 instance type?
- Which metric should you look at to measure contention?
- How do you manage fleets of containers at scale?
Datadog’s CTO, Alexis Lê-Quôc, presents the challenges and benefits of running Docker containers at scale. Alexis explains how to use quantitative performance patterns to monitor your infrastructure at the new level of magnitude and increased complexity introduced by containerization.
(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014Amazon Web Services
If you have tried Docker but are unsure about how to run it at scale, you will benefit from this session. Like virtualization before, containerization (à; la Docker) is increasing the elastic nature of cloud infrastructure by an order of magnitude. But maybe you still have questions: How many containers can you run on a given Amazon EC2 instance type? Which metric should you look at to measure contention? How do you manage fleets of containers at scale?
Datadog is a monitoring service for IT, operations, and development teams who write and run applications at scale. In this session, the cofounder of Datadog presents the challenges and benefits of running containers at scale and how to use quantitative performance patterns to monitor your infrastructure at this magnitude and complexity. Sponsored by Datadog.
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2l2Rr6L.
Doug Daniels discusses the cloud-based platform they have built at DataDog and how it differs from a traditional datacenter-based analytics stack. He walks through the decisions they have made at each layer, covers the pros and cons of these decisions and discusses the tooling they have built. Filmed at qconsf.com.
Doug Daniels is a Director of Engineering at Datadog, where he works on high-scale data systems for monitoring, data science, and analytics. Prior to joining Datadog, he was CTO at Mortar Data and an architect and developer at Wireless Generation, where he designed data systems to serve more than 4 million students in 49 states.
In this presentation, Mike walks through the philosophical shift of treating the servers that you have in-house as if they were part of a “cloud” and disposable, and then jumps into a technical demonstration of how to actually tear down and reconstruct your infrastructure at a moment’s notice.
Monitoring Docker at Scale - Docker San Francisco Meetup - August 11, 2015Datadog
In this session I showed building a multi-container app from beginning to end, using Docker, Docker-Machine, Docker-Compose and everything in between. You can even try it out yourself using the link in the deck to a repo on GitHub.
When running any amount of systems, gaining visibility into what they are doing can be a non-trivial matter. Starting on the path to monitoring can prove bumpy, and if you don’t measure, you don’t know. In this session, Michael Fiedler, Director of TechOps, will speak on personal experience with scalability, deployment, and monitoring challenges prior to using Datadog - and how that changed. He will cover how to get started, and examples of where monitoring the company's platform with Datadog provided the guiding light towards the team solving scalability problems.
In our last update we introduced Amazon CloudSearch. In this talk we're take it to the next level with a deep-dive on the service from the Amazon A9 team themselves. Hear the background on CloudSearch, as well as new features, new use cases, and new ways to access CloudSearch, and get to meet and question the team behind the service.
Monitoring and Scaling Redis at DataDog - Ilan Rabinovitch, DataDogRedis Labs
Think you have big data? What about high availability
requirements? At DataDog we process billions of data points every day including metrics and events, as we help the world
monitor the their applications and infrastructure. Being the world’s monitoring system is a big responsibility, and thanks to
Redis we are up to the task. Join us as we discuss how the DataDog team monitors and scales Redis to power our SaaS based monitoring offering. We will discuss our usage and deployment patterns, as well as dive into monitoring best practices for production Redis workloads
In this session, you get an overview of Amazon Redshift, a fast, fully-managed, petabyte-scale data warehouse service. We'll cover how Amazon Redshift uses columnar technology, optimized hardware, and massively parallel processing to deliver fast query performance on data sets ranging in size from hundreds of gigabytes to a petabyte or more. We'll also discuss new features, architecture best practices, and share how customers are using Amazon Redshift for their Big Data workloads.
(BDT401) Amazon Redshift Deep Dive: Tuning and Best PracticesAmazon Web Services
Get a look under the covers: Learn tuning best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your delivery of queries and improve overall database performance. This session explains how to migrate from existing data warehouses, create an optimized schema, efficiently load data, use work load management, tune your queries, and use Amazon Redshift's interleaved sorting features. Finally, learn how TripAdvisor uses these best practices to give their entire organization access to analytic insights at scale.
At BeeCon 2017 we related our experience with ADF and how we transitioned some solutions from Share to ADF. That was just the first chapter! Join us on our journey and learn how ADF has evolved from there and how we have leveraged new features, not to mention the upgrade process.
Strata 2016 - Architecting for Change: LinkedIn's new data ecosystemShirshanka Das
Shirshanka Das and Yael Garten describe how LinkedIn redesigned its data analytics ecosystem in the face of a significant product rewrite, covering the infrastructure changes that enable LinkedIn to roll out future product innovations with minimal downstream impact. Shirshanka and Yael explore the motivations and the building blocks for this reimagined data analytics ecosystem, the technical details of LinkedIn’s new client-side tracking infrastructure, its unified reporting platform, and its data virtualization layer on top of Hadoop and share lessons learned from data producers and consumers that are participating in this governance model. Along the way, they offer some anecdotal evidence during the rollout that validated some of their decisions and are also shaping the future roadmap of these efforts.
Architecting for change: LinkedIn's new data ecosystemYael Garten
2016 StrataHadoop NYC conference talk.
http://conferences.oreilly.com/strata/hadoop-big-data-ny/public/schedule/detail/52182
Abstract:
Last year, LinkedIn embarked on an ambitious mission to completely revamp the mobile experience for its members. This would mean a completely new mobile application, reimagined user experiences, and new interaction concepts. As the team evaluated the impact of this big rewrite on the data analytics ecosystem, they observed a few problems.
Over the past few years, LinkedIn has become extremely good at incrementally changing the site one mini-feature at a time, often in conjunction with hundreds of other incremental changes. LinkedIn’s experimentation platform ensures that it is always monitoring a wide gamut of impacted metrics with every change before rolling fully forward. However, when it comes to rolling out a big change like this, different challenges crop up. You have to rollout the entire application all at once; the new experience means that you have no baseline on new metrics; and existing metrics may see double digit changes just because of the new experience or because the metric’s logic is no longer accurate—the challenge is in figuring out which is which.
Shirshanka Das and Yael Garten describe how LinkedIn redesigned its data analytics ecosystem in the face of a significant product rewrite, covering the infrastructure changes that enable LinkedIn to roll out future product innovations with minimal downstream impact. Shirshanka and Yael explore the motivations and the building blocks for this reimagined data analytics ecosystem, the technical details of LinkedIn’s new client-side tracking infrastructure, its unified reporting platform, and its data virtualization layer on top of Hadoop and share lessons learned from data producers and consumers that are participating in this governance model. Along the way, they offer some anecdotal evidence during the rollout that validated some of their decisions and are also shaping the future roadmap of these efforts.
Presentation from RedDotRubyConf 2011 in Singapore. It explains multi-tenancy and why it is increasingly required for Rails development. Four of the many approaches are covered in some detail (including what resources we have available for re-use) and I end with a naive question (& call to action?) .. "Isn't it about time there was a 'Rails Way'?"
BDM39: HP Vertica BI: Sub-second big data analytics your users and developers...Big Data Montreal
Despite how fantastic pigs look with lipstick on and how magical elephants look with wings attached, there remains a large gap between what popular big data stacks offer and what end users demand in terms of reporting agility and speed. Join us to learn how Montreal-based AdGear, an advertising technology company, faced challenges as its data volume increased. You will hear how AdGear's data stack evolved to meet these challenges, and how HP Vertica's architecture and features changed the game.
(by Mina Naguib, Technical Director of Platform Engineering at AdGear).
https://youtu.be/tzQUUCuVjVc
Slidedeck for my session on Insider Dev Tour 2019 (Lisbon Jul 29th).
Mostly based on tools and platform support for AI workloads and the options for edge computing and cloud computing.
ML.NET, WinML, DirectML, Model Builder, Azure Cognitive Services, ...
Next Generation Vulnerability Assessment Using Datadog and SnykDevOps.com
Vulnerability assessment for teams can often be overwhelming. The dependency graph could be thousands of packages depending on the application. Triaging vulnerability data and prioritizing actions has historically been a very manual process, until now. With Datadog and Snyk, learn how to trace security and performance issues by leveraging continuous profiling capabilities for actionable insight that help developers remediate problems.
Join us on Thursday, January 21 for a unique opportunity to learn more about continuous profiling, vulnerability management, and the benefit to customers from using both of these products. In this webinar, you will:
Bust some myths around continuous profiling and learn how Datadog differentiates itself
See decorated traces in action for sample Java applications and understand how Snyk + Datadog reduce time to triage supply chain vulnerabilities
Learn roadmap information for upcoming public announcements from both partners
The Node.js Foundation has consolidated all the best thinking around why enterprises should consider Node.js for their systems of engagement in this short presentation.
NDC Sydney 2019 - Microservices for building an IDE – The innards of JetBrain...Maarten Balliauw
Ever wondered how IDE’s are built? In this talk, we’ll skip the marketing bit and dive into the architecture and implementation of JetBrains Rider.
We’ll look at how and why we have built (and open sourced) a reactive protocol, and how the IDE uses a “microservices” architecture to communicate with the debugger, Roslyn, a WPF renderer and even other tools like Unity3D. We’ll explore how things are wired together, both in-process and across those microservices. Let’s geek out!
Microservices as an evolutionary architecture: lessons learnedLuram Archanjo
Over the years the architecture of microservices has been widely adopted, since it provides numerous advantages such as: technological heterogeneity, scalability, decoupling and so on.
In this sense the microservices architecture meets the definitions of an evolutionary architecture, that is, an architecture designed for incremental changes even changes of languages.
In this lecture, we will discuss the decisions to adopt frameworks and techniques such as: Spring, Vert.x, gRPC, Event-driven Architecture in an architecture for a payment medium solution in which throughput and response time is crucial for the survival of the business .
After I attended Google IO 2014, I wanted to present what is new for Android Lollipop from a Developer perspective.
This presentation covers almost everything except, maybe, native Android Wear development, Android Auto and Android TV
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.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
15. How do you help me deal with:
N components: mongo, redis, nodejs, ...
x P environments: prod-1, prod-2, staging, …
x Q versions: app-blue, app-green, etc
x R users
29. CloudFormation++
. a CFN template usually has related
dashboards and alerts.
. same life-cycle
e.g. app tier:
. dashboards for ELB and front-end instances
. alerts on HTTP errors, etc
