From Cardinal(ity) Sins to Cost-Efficient Metrics Aggregation
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Are you collecting just about every metric under the sun and the kitchen sink too? Understanding the cost of collecting metrics and the usefulness of those metrics is the only way to scale in a cloud native world. You can’t get away with just collecting everything as you grow. How can you make decisions about what to collect, what to drop, what to aggregate while still being able to alert, triage, remediate? Gain immediate insights into high cost data (DPPS), when to drop time series data, and how to determine when the value of that data is at its lowest.
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Cloud-Native Fundamentals: Accelerating Development with Continuous Integration
Cloud-Native Fundamentals: Accelerating Development with Continuous Integration
Connecting Kafka to Cash (CKC) (Lyndon Hedderly, Confluent) Kafka Summit Lond...
Connecting Kafka to Cash (CKC) (Lyndon Hedderly, Confluent) Kafka Summit Lond...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
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Outsourcing IT Projects to Managed Hosting of the Cloud
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Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized E...
Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized E...
IRJET- Predicting Bitcoin Prices using Convolutional Neural Network Algor...
IRJET- Predicting Bitcoin Prices using Convolutional Neural Network Algor...
When Data Visualizations and Data Imports Just Don’t Work
When Data Visualizations and Data Imports Just Don’t Work
Adtech scala-performance-tuning-150323223738-conversion-gate01
Adtech scala-performance-tuning-150323223738-conversion-gate01
Enhancing Data Security in Cloud Storage Auditing With Key Abstraction
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More from Paige Cruz
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
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:
Observability Concepts EVERY Developer Should Know (DevOpsDays Seattle)
Because observability is such a broad topic – and often something we learn on the job – it can feel like there’s too much to learn at once. But you don’t have to tackle everything and can start with the basics and build from there!
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.
No matter what tooling is in place, there are still observability fundamentals that developers should know. That’s why I’ve put together a primer on the different telemetry types, when to use them, how to understand the data journey, and what to look for in time series graphs.
Power Up with Podman - Kubernetes Community Day LA
Curious about containers beyond Docker? There’s a new generation of containers on the scene, Podman! Supporting secure, rootless containers for Kubernetes microservices, it was designed and built with the cloud in mind. Benefitting from the lessons learned out in the open from Docker, this next generation of containers will quickly become a trusted daily driver in your dev workflow.
Covering what you need to know as an end-user from the UI to the backend, sharing a real world use case leveraging Podman for open source observability workshops https://o11y-workshops.gitlab.io. Paige will share how Podman and the adorable seal mascots Caitlín, Maighréad and Róisín have transformed her local development!
99.99% of Your Traces Are (Probably) Trash (SRECon NA 2024).pdf
Distributed tracing is still finding its footing in many organizations today, despite being an industry concept for 14 years! One challenge to overcome is managing the data volume. Keeping 100% of traces is expensive and unnecessary - enter sampling. From head-based, tail-based or mixing and matching there is a buffet of configuration options available with OpenTelemetry. Let’s review the tradeoffs associated with different sampling configurations and their impact to the cost and value of your tracing data.
OTel Orientation: How to Train Teams (OTel in Practice)
This document provides guidance on training teams in observability using OpenTelemetry. It discusses identifying learning gaps and developing training workshops. A case study example is provided of an "OpenTelemetry 101: Let's Instrument!" workshop that teaches developers how to instrument applications with OpenTelemetry. The workshop uses a sample application and Jaeger to demonstrate OpenTelemetry concepts and skills. Further resources on practical learning theory and OpenTelemetry documentation are also referenced.
Avoiding Alert Bankruptcy and Burnout
The signal to noise ratio can be frustratingly high for on-call alerts and downright mystifying when joining a new company or rotation. If you treat PagerDuty like the boy who cried wolf you’ve certainly mired in monitoring debt. Monitoring debit is tragically common and with investment mitigatable! Just how much of a risk are false positives? The data shows that a high number of false alerts trains workers to assume most alerts will be false. Repetition of the same alerts causes even greater alert fatigue. For clinicians the likelihood of acknowledging an alert dropped 30% for each reminder. Paige will share the nuts and bolts of how to start auditing your own alerts to begin your journey towards an on-call oasis.
Tracing Adventures from PR - Production
Many things can go awry on the journey from pull request (PR) open to merge to production deployment. Issues can arise from the application code, layers of YAML configuration, underlying infrastructure or pipeline logic itself. How can distributed tracing and trace-derived metrics bring developers and operators together for troubleshooting paradise? I’ll unpack a deploy gone bad from both vantage points, gaining an empathy for the engineer who needs to deploy their changes and an ops engineer who is responsible for keeping the system up and running. With signals from OpenTelemetry I will show how increasing the observability of your deploy system can facilitate better collaboration and quicker troubleshooting.
Threat Modeling in the Cloud
Threat modeling is a key part of securing your cloud computing environment and is unique to each organization's people, practices and processes. Without a threat model you could end up going on wild goose chases and miss the forest for the trees. This talk will introduce the concept of threat modeling including how to get started, guiding questions and recap findings from the Argo Project Threat Model from 2021. Learn how and why to start threat modeling today!
There's No Place Like Production
There’s a reason “i test in prod” isn’t a cheeky take but a lived reality. And that reason is there is no place like production. Not local dev or staging or other environment. This became clear when I deployed a tiny config change that passed all checks, reviews and pre-production environments that triggered a SEV-1.
Examining each step of the journey from PR to production I uncovered the snafu that had occurred (unsurprisingly it relates to overwriting key blocks on nested YAML files).
I’ll share how difficult it was to reconstruct the chain of events in the system compared to the ideal case of a highly observable system and how to share your own incident learnings since we all test in prod!
Taming Feral DevOps
The misunderstanding that devops is a tool or team or role has tragically increased the gulf between developers and operators.If you have been unofficially on-call 24/7, toiled away in turmoil, managed initiatives across multiple silos sans project manager with a directive to “influence without authority”...surprise you have lived the contradiction that is feral devops!
Consequences of letting this fester are: burn out, learned helplessness and missing out on the speed that happens when developers and operators communicate openly. Taming feral devops is a journey you can start by gathering feedback on the status quo, iterating on onboarding and training and holistically examining on-call health.Whether you’re an individual contributor, manager or leader you will find ideas to experiment with to “domesticate” devops in your organization
SRECon23 Cognitive Apprenticeship in Action_ Alert Triage Hour of Power
Cognitive apprenticeship is the philosophy that it is more effective to learn in context and real-world situations compared to following a tutorial in a sandboxed environment. In a nutshell it is “learning-through-guided-experience” and shines when teaching problem-solving processes experts use to handle complex tasks like say…investigating an alert by spelunking in production observability and monitoring data. Learn how Alert Triage Hour of Power became a can’t miss meeting of camaraderie and system surprises!
Pushing Observability Uphill - The Single “Pain” of Glass
For years tech companies have chased the fabled “single pane of glass” , the one observability tool to understand your system from north to south and east to west. Leafing through promo materials promising instant insights and seamless turnkey integrations you’d think increasing system observability is as easy as assembling a Lego set.
In my experience chasing the “single pane of glass” translates to “pain in the ass”. Survey data supports this revealing the majority of engineers cite tool sprawl as a minor or non-existent problem despite relying on several tools. As alluring as the siren call of “single pane of glass” is, let's be practical and examine how to best observe systems across a myriad of tooling.
From the telemetry buffet of metrics, events, traces and logs learn when to reach for which type and ways to bridge the gaps with links and enhance with context to free yourself from the fool’s errand of a “single pane of glass”.
Power Up with Podman
Curious about containers? There’s a new generation of containers on the scene, Podman! Supporting secure, rootless containers for Kubernetes microservices, it was designed and built with the cloud in mind. Benefitting from the lessons learned out in the open from Docker, this next generation of containers will quickly become a trusted daily driver in your dev workflow.
Covering what you need to know as an end-user from the UI to the backend, sharing a real world use case leveraging Podman for open source observability workshops https://o11y-workshops.gitlab.io. Paige will share how Podman and the adorable seal mascots Caitlín, Maighréad and Róisín have transformed her local development!
Intro to Instrumentation
This document provides an introduction and overview of instrumentation using OpenTelemetry. It begins with defining key concepts of observability and distributed tracing. It then discusses OpenTelemetry's SDKs, exporters and collectors for instrumenting code and exporting telemetry data. The document demonstrates both automatic and manual instrumentation techniques in OpenTelemetry and shows how to visualize trace data in Jaeger. It concludes by mentioning OpenTelemetry community resources for further learning.
99.9% of Your Traces are Trash
Distributed tracing is still finding its footing in many organizations today, one challenge to overcome is the data volume - keeping 100% of your traces is expensive and unnecessary. Enter sampling - head vs tail how do you decide? Let’s review the tradeoffs associated with different types of sampling strategies and how they can be mixed and matched.
3rd Wave Observability: Open or Bust
This document discusses the evolution of observability from network/device monitoring (Wave 1) to application performance monitoring (Wave 2) to the current focus on observability (Wave 3). It notes that observability moves past proprietary data formats and interdependence of early solutions by enabling instrumentation once and observation anywhere. The document advocates for teams to own end-to-end observability of their services and dependencies, and notes that observability data can help teams understand where to invest engineering time to most directly impact customers and business goals.
More from Paige Cruz (16)
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know (DevOpsDays Seattle)
Observability Concepts EVERY Developer Should Know (DevOpsDays Seattle)
Power Up with Podman - Kubernetes Community Day LA
Power Up with Podman - Kubernetes Community Day LA
99.99% of Your Traces Are (Probably) Trash (SRECon NA 2024).pdf
99.99% of Your Traces Are (Probably) Trash (SRECon NA 2024).pdf
OTel Orientation: How to Train Teams (OTel in Practice)
OTel Orientation: How to Train Teams (OTel in Practice)
SRECon23 Cognitive Apprenticeship in Action_ Alert Triage Hour of Power
SRECon23 Cognitive Apprenticeship in Action_ Alert Triage Hour of Power
Pushing Observability Uphill - The Single “Pain” of Glass
Pushing Observability Uphill - The Single “Pain” of Glass
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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!
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Apps Break Data
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
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Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
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HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
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- How do CCB and CCX licenses really work?
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- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Dandelion Hashtable: beyond billion requests per second on a commodity server
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
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Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.AppSec PNW: Android and iOS Application Security with MobSF
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
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Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
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Charlie Greenberg, host
Fueling AI with Great Data with Airbyte Webinar
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
JavaLand 2024: Application Development Green Masterplan
My presentation slides I used at JavaLand 2024
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
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From Cardinal(ity) Sins to Cost-Efficient Metrics Aggregation
- 1. chronosphere.io From Cardinal(ity) Sins to Cost Efficient Metrics Aggregation Paige Cruz, retired SRE open source observability advocate
- 2. chronosphere.io CFO looking at the o11y bill
- 6. Cloud Native Observability bills are outrageous
- 7. Cloud Native Data Growth 7 Cloud (IaaS, VM-based) 2008 - 2018 Cloud Native (Microservices and Containers) 2018 - ? On-Premises (Data center) 1998 - 2008 Business Increase in Scale Observability Data Increase in Scale *Source: ESG Distributed Cloud Series: Observability, Feb 2022, Scott Sinclair and Rob Strechay
- 8. chronosphere.io Most recently [vendor] was looked at to help monitor a small Kubernetes test cluster. 3 nodes. Now the base rate of $18/mo is fine…except now they charge $1 per container per month past 10 containers per host. Since K8s (depending on how you install it) runs a bunch of little containers handling various back end things, you might not deploy anything to the cluster and still be WAY over that 10 container limit. In our case it came out to like $200/mo to monitor 3 nodes - that were nowhere fully loaded. - Hacker News thread
- 9. chronosphere.io Data volume Experiment: - Hello World app on 4 node Kubernetes cluster with Tracing, End User Metrics (EUM), Logs, Metrics (containers / nodes) - 30 days == +450 GB
- 10. Mighty Metrics
- 11. “ 1 in 10 metrics are actually directly queried - ServiceNow
- 12. Contributing Factors to the Metrics Bill 12 How many things you’re monitoring # of containers and infra components How often each metric is scraped Metric Granularity How long you keep the data Retention Window How many unique combos of dimensions on metrics Cardinality 12
- 13. 13
- 14. 14 Cost of monitoring can be a factor in determining how quickly to deprecate or sunset features/services/environments # of containers and infra components 14
- 15. 15 Emission time = adjust scrape_interval (from 10s samples -> 30s samples) Ingest time = aggregate Over time post-storage = downsampling Metric Granularity 15
- 17. 17 For operational metrics……most (99.9%) of queries do not pass 7 days but average retention at original granularity ranges from 2-4 weeks Retention Window 17
- 18. 18 Low value tags or entire metrics should be dropped as early as possible Dropping Data 18
- 21. “ What is the value of this metric? - You, when auditing metrics
- 22. Auditing Your Metrics 22 22 ● Scope what your team is responsible for ○ filter queries with team:YOURS ● Identify easy wins. Metrics that aren’t ○ In a monitor definition ○ Directly queried by end users ○ Powering charts for visited dashboards ● Identify labels that are unnecessary ○ e.g. prometheus instance label or instance_type ● Share your successes!
- 23. 23 23
- 24. 24 24 CFO looking at the cost efficiency of metrics
- 25. Resources - How Gloo uses the OTel Collector to drop metrics/labels and provide the Minimum Metrics Set - How to drop and delete metrics in Prometheus - How can recording and data roll-up rules help your metrics? - Observability is Too Damn Expensive - DevOpsDays London
- 26. Catch up with me: - Rescuing On-Call Engineers (send your manager) - KubeCon OTel 101: Let’s Instrument! (tracing) workshop - There’s No Place Like Production Conf42 Incident Management paigerduty@ chronosphere.io hachyderm.io LinkedIn
- 27. Q&A