Oracle announced new capabilities to help customers accelerate the development of applications and deployment on Oracle Cloud Infrastructure (OCI).
The Crowdstrike outage has created no shortage of commentary, speculation, and armchair analysis on exactly how such a massive failure could occur. The level of discussion and scrutiny is warranted, most agree this is probably the largest IT outage in history. The impact on Crowdstrike's stock price was immediately felt, causing shares to tumble dramatically in the wake of the incident.
As of this writing, we don't have an official post-incident analysis, but most observers agree that the global outage was due to a code deployment that skipped quality checks before it was deployed.
The knee jerk response of a "How could someone possibly let this happen" is both clueless and misinformed. Oh, if I could only alleviate your fears and somehow console you that this is an uncommon issue in the software development lifecycle. If only we were all so pious in our practices, processes, and methodologies that deployments like this were a microcosm of technology systems. If only the controls we put in place were fool proof, unbreakable, and predictable.
Rather than disparage the incident as a careless mistake taken on by uniformed or under achieving engineers, we should take a page from some of the highest achievers in resiliency, reliability, and scale in the technology sector. Let us strive to consider the outage in a blameless mindset. If you remove the actor from the situation, and reframe the outage based on the facts and data of the incident, you suddenly begin to start asking the right questions. Namely, "Why?"
Incident response practices don't stop at the first "Why?", though. We must strive to fully understand the root cause of the incident, and so a blameless post mortem culture scrutinizes the facts of an incident until satisfied that the true indication of the why is understood.
Perhaps the build systems were experiencing errors. Maybe the deploy process was being circumvented to hit a business deadline (a technologist's favorite scenario). Maybe (one of my favorite sources of outages) an entire team reviewed the code in question, line by line, and all agreed that it "Looks Good To Me" and blessed the deployment with another of my favorite cliches, "Ship It!"
The harsh reality is that all who work in technology are one bad push away from experiencing their own personally inflicted Crowdstrike hellscape. And, a more sobering take is that we don't always recognize the "bad code" until it is well underway, causing chaos and pain for all of our stakeholders.
Perhaps those of us with smaller market shares and less global presence should take solace in the fact that due to our size and market share, we'll never experience anything this bad. Perhaps.
In light of this historical event, may I suggest that we take a moment to reflect on ourselves and strive to get our own respective houses in order. Let's take a moment to reassess our own DevOps practices, and see what we can shore up before the inevitable happens.
Reassessing Your DevOps Practices
The Crowdstrike outage serves as a stark reminder that all systems, no matter how great or small, are not immune to failures. We can lean into some of the core tenets of the DevOps philosophy to guide our self-analysis.
Embrace a Culture of Continuous Improvement
DevOps is not a set-it-and-forget-it approach. And you're never really "finished" with a DevOps practice. As your business goals change and your technology matures, new challenges and unforeseen variability will constantly challenge your team. Create a culture that regularly reviews and refines your processes, tools, and practices. Encourage an environment where feedback is regularly given, welcomed, and acted upon.
Continuous Integration, Continuous Deployment
The build and integration phase of the software lifecycle is the most important time to scrutinize code. Automated testing, linting, and ad-hoc test environments are all excellent technical resources for catching bugs before they are released. But with any good DevOps practice, this foundational skill asks almost as much from the engineers as the machines. Training teams to integrate their code changes daily, reducing the amount of time an engineer writes code in isolation, and treating each change set as the code that can be deployed at any moment creates a constant and high-fidelity feedback loop. By bringing potential bugs and outage-creators to constant scrutiny, the net effect is that you'll ship more resilient code, more often.
Become an Incident-Centric Operation
Notice, though, I said "more often," not "always". The harsh reality is that even if you achieve the zen-like state of continuous integration and deployment, you will have incidents. Read that again.
If we know that an incident is always around the corner, we can invest in preparing our teams for the inevitable. Standardize a practice of incident response that prepares your team to respond in the most efficient way possible. Codify the practice of documenting incident timelines and post incident reports. Dedicate time for a wide group of your engineering teams to review incidents, and create plans of action to remediate them. Build out your product roadmap so that you prioritize fixing, triaging, and extending the learnings you've gained from the formalized practice of incident response. Set roles, responsibilities, and sustainable incident response schedules so your team can confidently navigate outages when they occur.
The investment you make in your incident response practice will create happier customers, resilient systems, cross-functional teams, and a shared ownership of the success of your business.
Invest In Monitoring and Observability
It's not sufficient to know that your Kubernetes cluster has oodles of headroom and can scale to global traffic if your customers are fed up with the constant work-arounds they have to implement to work with your application. Observability today is more than just knowing your machines are happy.
With increasing standardization in open source observability tools like OpenTelemetry, understanding your customer experience is as achievable as knowing when your virtual machine is going to run out of disk space. Introducing an observability stance that embraces tracing, logs, and metrics means you can see the incident before it comes knocking on your door.
Instrumenting your code to achieve observability, like all good practices, doesn't reside solely on the machine. The practice of instrumenting your code should feel very similar to your adherence to Test Driven Development (you are doing TDD, right?). Instrument the code before you implement it. Create fast feedback loops during the development process so your teams can see their metrics in your favorite observability platform as they build your next exciting feature.
Break Down Silos
I'd wager most blog posts about DevOps proclaim this same adage, in various contexts. Perhaps the frequency in which this directive is echoed is a signal for how extremely difficult it is to achieve. If there is one point of reflection to prioritize, above all others, I would say this is it.
It would be extremely difficult and irresponsible to prospectively say that there's "one weird trick" to breaking down silos for your specific challenges. To use my favorite phrase in consulting, the reality is, "it depends."
I will say, though that my experience as of late with the practices of DevOps, in all the forms that implement them, be it Site Reliability Engineering, Platform Engineering, Cloud Engineering, or any form of technology operations, is that we have a serious problem with silo building this subdiscipline.
The promise of DevOps was that we would bridge the chasm between getting production code out into the wild and actually generating it. My guess is many of our teams are working away in complete ignorance of the carefully crafted silo that they've inadvertently created for themselves.
This form of reflection takes the most honest scrutiny. Consider some prompts for reflection:
How aware is your DevOps team about another team's roadmap, OKRs, and development practices?
When was the last time you sat down and paired with an engineer on another team to help them debug an issue they've found in their code in a pre-production environment?
Do your senior, staff, and principal engineers on your DevOps teams attend stand ups, planning, and retros across the organization?
When was the last time you embedded one of your Cloud Engineers on a front end team?
As much as I hate to admit, this point of reflection is arguably the most negatively impacted by technology. For all of the other points I've raised, the challenges they face are augmented and improved by thoughtfully applying technology to facilitate efficiency in enacting a practice.
This one, though, is driven by humans, and for humans. But, with all of these reflection points, the benefits of this investment are massive.
Another critical outage is absolutely on the horizon. Don't waste your time with schadenfreude. Reassess your DevOps practices and prepare for the coming storm. Even if your own outages pale in comparison to the impact of the Crowdstrike incident, that outage is the most important because it is yours. Plan accordingly.
Industry News
JFrog and GitHub unveiled new integrations.
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Red Hat announced the general availability of Red Hat Enterprise Linux (RHEL) AI across the hybrid cloud.
Jitterbit announced its unified AI-infused, low-code Harmony platform.
Akuity announced the launch of KubeVision, a feature within the Akuity Platform.
Couchbase announced Capella Free Tier, a free developer environment designed to empower developers to evaluate and explore products and test new features without time constraints.
Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, announced the general availability of AWS Parallel Computing Service, a new managed service that helps customers easily set up and manage high performance computing (HPC) clusters so they can run scientific and engineering workloads at virtually any scale on AWS.
Dell Technologies and Red Hat are bringing Red Hat Enterprise Linux AI (RHEL AI), a foundation model platform built on an AI-optimized operating system that enables users to more seamlessly develop, test and deploy artificial intelligence (AI) and generative AI (gen AI) models, to Dell PowerEdge servers.
Couchbase announced that Couchbase Mobile is generally available with vector search, which makes it possible for customers to offer similarity and hybrid search in their applications on mobile and at the edge.
Seekr announced the launch of SeekrFlow as a complete end-to-end AI platform for training, validating, deploying, and scaling trusted enterprise AI applications through an intuitive and simple to use web user interface (UI).
Check Point® Software Technologies Ltd. unveiled its innovative Portal designed for both managed security service providers (MSSPs) and distributors.
Couchbase officially launched Capella™ Columnar on AWS, which helps organizations streamline the development of adaptive applications by enabling real-time data analysis alongside operational workloads within a single database platform.