Ibukun Itimi

Speed-first pipelines may look efficient, but they rarely hold up under compliance, scale, and reliability demands. For SaaS teams, CI/CD automation isn’t just about deploying faster—it’s about building delivery systems that stay stable as change accelerates. When pipelines are consistent and automated, teams release with confidence, recover faster, and reduce operational risk. Read our blog to learn more: https://lnkd.in/gBRNDK-Q #DevOpsAutomation #CICDPipelines #SaaSDevOps #CloudEngineering #PlatformEngineering #InfrastructureAsCode #SiteReliability #DevOpsConsulting #impressico

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CEO Jon C. said it right: reviewing telemetry isn’t glamorous. In fact for most companies it's delayed, painful, and sometimes even impossible. Nominal's proud to accelerate the vital, unglamorous work of our customers. We help Vital Lyfe complete telemetry review in minutes, not days – so their systems can keep pushing water through deserts, disaster zones, and coastlines outside any grid. Old industry, new playbook. All systems Nominal!

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APM budgets grow. MTTR doesn't. The problem isn't spending, it's strategy. Cloud-native systems fail across distributed processes in seconds. Traditional tools respond with agent sprawl and blanket data collection. This mismatch, static tools chasing dynamic failures, creates data floods that bury the critical context you need. OpenResty XRay flips the model: dynamic post-mortem analysis. Instead of collecting everything, we capture high-fidelity snapshots automatically when failures occur: 1. Fully Dynamic Post-Mortem Analysis: Abandon the resource consumption of 24/7 full data collection. Only when abnormal fluctuations occur in CPU, memory, or I/O, the system will automatically trigger analysis, precisely recording the stack and context when the failure occurred. This allows developers to conduct reviews based on real "black box" data, rather than relying on guesswork to reconstruct the scene. 2. Thorough Zero-Intrusion: Utilizing dynamic tracing technology, no need to modify a single line of code, no need for restarts, and not even needing Debug Symbols, directly see through the operational details of the production environment. 3. De-Sidecar-ization: In a K8s environment, directly cut in from the host machine side, avoiding complex Sidecar maintenance costs and intrusion into container images. 4. Binary-Level Security Compliance: Vulnerability scanning driven by binary evidence, directly seeing through running processes, completely getting rid of the false positive traps of version number matching. Whether it's LTS Backport patches or compiler optimization trimming, it can be accurately identified, allowing security teams to say goodbye to "interpretive compliance" and return to high-value work. The future of observability should not be more expensive storage bills, but deeper, lower-level system insight. Regarding how OpenResty XRay achieves fully dynamic post-mortem diagnosis, you can check out this in-depth analysis: https://lnkd.in/gu8hWAHy #OpenResty #Observability #DynamicTracing

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With tight iOS privacy rules, almost 40–60% of installs go unattributed (or at least mis-attributed) on many tools. That means you can be spending on ads, while half your data is invisible. If only there was something to help you reclaim ~95% of that, and use creative-level performance to guide how to optimize for retention, LTV, and player engagement... Oh nevermind, there is Audiencelab by Geeklab. https://audiencelab.ai/

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You don’t control how third-party mobile apps are built. You don’t control their SDK choices. You don’t control their update cadence. But you do own the risk. Learn how to evaluate and govern mobile apps with confidence: https://loom.ly/0_JvPY0 #ThirdPartyRisk #EnterpriseRisk #MobileRisk #MobileSecurity #AppSecurity

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Most teams track engineering hours, infrastructure, and AI costs. But one major expense often goes unnoticed: clarification loops. Unclear requirements create back-and-forth, slow delivery, and more rework. With AI, vague inputs become even more expensive. Learn how input quality directly impacts delivery cost↓

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How CTOs secure API integrations for B2B payment gateways? Learn fraud prevention, API hardening, and best practices in fintech security.

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One small realization that unlocked a lot of clarity: Primitives describe values. Semantics describe intent. Good systems keep them separate. Applies to design systems, APIs, and architecture in general.

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Traditional incident response fails in microservices. Learn why, and discover the framework for incident response in microservices architecture with real-world examples.

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🚀 Pulsar Guide for Kafka Engineers (Part 2) - Tenants, Namespaces & Bundles 🔍 This post dives into Pulsar’s multi-tenancy model—tenants, namespaces, and bundles—and how it compares to Kafka’s single-tenant architecture. Learn how Pulsar isolates workloads, simplifies topic management, and enables seamless load balancing across brokers. 🧠 Built for Kafka engineers. Backed by Pulsar experts. (Penghui Li, Hang Chen, Neng Lu) 👉 Read now: https://hubs.ly/Q03BmcD10 #ApachePulsar #Kafka #StreamingData #CloudNative

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The era of waking up at 3 AM to fix a crashed server is officially over. If your DevOps team is still manually responding to every system alert, your operational model is holding your business back. In 2026, elite engineering teams have moved beyond simple CI/CD automation and are deploying Self-Healing Infrastructure. Currently, 73% of enterprises are implementing AIOps specifically to combat "alert fatigue" and reduce manual toil. We are seeing a massive shift where systems don't just page an engineer when something breaks—they analyze the telemetry data, identify the exact root cause (like a memory leak), and autonomously adjust resource limits or roll back the deployment in real-time. This changes everything. DevOps engineers are evolving from reactive "pipeline mechanics" into strategic system designers who govern intelligent, autonomous agents. At Apex IT Solutions, we help global enterprises integrate intelligent AIOps into their infrastructure. We build platforms that monitor, detect, and self-correct—ensuring maximum uptime and freeing your best talent to focus on innovation instead of endless incident response. Is your infrastructure smart enough to fix itself, or are your engineers still doing the heavy lifting? https://lnkd.in/d3jdGubA #DevOps #Serverless #CloudNative #PlatformEngineering #ITInfrastructure #SoftwareEngineering #TechTrends2026

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🚀 Are your pull requests slowing your team down? Most teams treat every pull request the same. But not every change needs the same level of attention. That’s where Ship / Show / Ask comes in. With DevSensei, you can structure your PR workflow into three simple categories: ✅ Ship For small, low-risk changes. No need to wait, just merge and move on. 👀 Show For changes you want visibility on, but without blocking progress. 💬 Ask For complex work that needs discussion and proper review. This approach helps teams: • Reduce waiting time on trivial PRs • Focus reviews where they actually matter • Keep delivery speed high without sacrificing quality Instead of one rigid process, you get a workflow that adapts to the change itself. Because not every PR should slow you down. 👉 Curious how it works in practice?

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