Site Reliability Engineering Certified Professional - SRECP

Site Reliability Engineering Certified Professional - SRECP The Site Reliability Engineering Certified Professional (SRECP) certification course by DevOpsSchool

If you’re building Terraform/CloudFormation modules (or any IaC “building blocks”) and you’re tired of copy-paste infras...
18/02/2026

If you’re building Terraform/CloudFormation modules (or any IaC “building blocks”) and you’re tired of copy-paste infrastructure, broken upgrades, and unreadable variables, this guide is a practical engineer’s playbook to design **reusable IaC modules** that stay clean, stable, and easy to adopt—covering **naming conventions, inputs/outputs, validation, versioning, and upgrade patterns** you can apply immediately.

Reusable IaC isn’t about “more modules.” It’s about **better interfaces** and **predictable change**:

✅ **Naming** → consistent, searchable, team-friendly conventions
✅ **Inputs** → minimal + well-typed variables, defaults, and validation
✅ **Outputs** → stable contracts that consumers can rely on
✅ **Versioning** → semantic versioning + clear breaking-change rules
✅ **Structure & docs** → examples, README patterns, and module boundaries that scale

Read here:
[https://www.cloudopsnow.in/reusable-iac-module-design-naming-inputs-outputs-versioning-the-engineers-playbook/](https://www.cloudopsnow.in/reusable-iac-module-design-naming-inputs-outputs-versioning-the-engineers-playbook/)

If you’re adopting GitOps (or struggling to scale it), this article breaks down **Argo CD vs Flux** in plain engineering...
18/02/2026

If you’re adopting GitOps (or struggling to scale it), this article breaks down **Argo CD vs Flux** in plain engineering terms and then goes deeper into the **patterns that work in real teams**—and the **anti-patterns** that quietly create drift, outages, and “GitOps theater.”

GitOps isn’t just “deploy from Git.” It’s a discipline:

✅ **Declare everything** (apps + infra) as code in Git
✅ **Automate reconciliation** so the cluster matches desired state
✅ **Use safe promotion paths** (dev → staging → prod) with approvals
✅ **Avoid common traps** (manual kubectl changes, shared namespaces, messy repo layouts, unreviewed hotfixes)

Read here:
[https://www.cloudopsnow.in/gitops-explained-argo-cd-vs-flux-patterns-and-anti-patterns/](https://www.cloudopsnow.in/gitops-explained-argo-cd-vs-flux-patterns-and-anti-patterns/)

If you’re choosing an Infrastructure-as-Code tool and tired of marketing comparisons, this guide breaks it down in an en...
15/02/2026

If you’re choosing an Infrastructure-as-Code tool and tired of marketing comparisons, this guide breaks it down in an engineer-first way—showing when **Terraform vs CloudFormation vs Pulumi** fits best, based on team skills, scale, governance needs, and day-to-day workflows (with practical decision criteria, not theory).

Most teams don’t fail at IaC because the tool is “bad.” They fail because the tool doesn’t match how the team builds, reviews, secures, and operates infrastructure.

✅ **Terraform** → best for multi-cloud + strong ecosystem + reusable modules
✅ **CloudFormation** → best for AWS-native teams that want tight AWS integration + guardrails
✅ **Pulumi** → best for dev-heavy teams that want IaC in real programming languages + shared app/platform patterns

Read here:
[https://www.cloudopsnow.in/terraform-vs-cloudformation-vs-pulumi-which-fits-which-team-the-practical-engineer-first-guide/](https://www.cloudopsnow.in/terraform-vs-cloudformation-vs-pulumi-which-fits-which-team-the-practical-engineer-first-guide/)

If you’re starting with Terraform (or you’ve used it but still feel shaky on “modules vs state vs workspaces”), this gui...
11/02/2026

If you’re starting with Terraform (or you’ve used it but still feel shaky on “modules vs state vs workspaces”), this guide is a clean, engineer-friendly walkthrough that explains the fundamentals **with real examples**—and shows how to build Terraform in a maintainable, production-ready way.

Terraform becomes easy when you follow a simple path:

✅ **Core concepts** → providers, resources, variables, outputs (and how plans really work)
✅ **Modules** → reuse infrastructure like “packages” (structure, inputs/outputs, versioning)
✅ **State** → why remote state matters, locking, drift, and safe workflows
✅ **Workspaces** → when to use them (and when not to) for env separation
✅ **Best practices** → naming, folder layout, secrets handling, CI/CD, linting/testing, and guardrails

Read here:
[https://www.cloudopsnow.in/terraform-for-beginners-modules-state-workspaces-best-practices-with-real-examples/](https://www.cloudopsnow.in/terraform-for-beginners-modules-state-workspaces-best-practices-with-real-examples/)

If you build or operate production systems, this article is a practical, engineer-friendly guide to the **reliability pa...
10/02/2026

If you build or operate production systems, this article is a practical, engineer-friendly guide to the **reliability patterns that keep services alive under real-world failures**—with clear explanations of **retries, timeouts, circuit breakers, and bulkheads**, plus how to apply them without causing retry storms, cascading failures, or hidden latency spikes.

Most outages don’t start as “big failures.” They start as small slowdowns that cascade. These patterns help you stop the cascade:

✅ **Retries** → only when safe (use backoff + jitter, retry budgets, and idempotency)
✅ **Timeouts** → set strict limits (no infinite waits; align client/server timeouts)
✅ **Circuit Breakers** → fail fast when dependencies degrade (protect latency + threads)
✅ **Bulkheads** → isolate blast radius (separate pools/queues per dependency or tier)

Read here:
[https://www.cloudopsnow.in/reliability-patterns-that-keep-systems-alive-retries-timeouts-circuit-breakers-bulkheads/](https://www.cloudopsnow.in/reliability-patterns-that-keep-systems-alive-retries-timeouts-circuit-breakers-bulkheads/)

If you’re running microservices and you want **real performance confidence** (not just “it worked in staging”), this eng...
10/02/2026

If you’re running microservices and you want **real performance confidence** (not just “it worked in staging”), this engineer-friendly guide walks through **how to plan and execute performance testing for microservices** using **k6 + JMeter**, with a practical strategy, the right KPIs, and a repeatable approach you can use in CI/CD.

Performance testing becomes simple when you run it as a clear workflow:

✅ **Strategy** → define user journeys, service boundaries, test types (load/stress/spike/soak), and realistic traffic models
✅ **KPIs** → focus on the metrics that matter (p95/p99 latency, error rate, throughput, saturation, queue/backlog, DB/cache latency)
✅ **Ex*****on** → build tests in k6/JMeter, run baseline → ramp → breakpoints, isolate bottlenecks, validate fixes, and automate regression runs

Read the full practical guide here:
[https://www.cloudopsnow.in/performance-testing-for-microservices-k6-jmeter-strategy-kpis-a-practical-engineer-friendly-guide/](https://www.cloudopsnow.in/performance-testing-for-microservices-k6-jmeter-strategy-kpis-a-practical-engineer-friendly-guide/)

If you’re an engineer who’s tired of scaling “by gut feel,” this article is an engineer-friendly playbook for **cloud ca...
07/02/2026

If you’re an engineer who’s tired of scaling “by gut feel,” this article is an engineer-friendly playbook for **cloud capacity planning**—how to translate **CPU, memory, QPS, latency, and scaling limits** into real decisions (what to scale, when to scale, and how to avoid overprovisioning while still protecting performance).

Capacity planning isn’t just “add more nodes.” It’s a repeatable loop:

✅ **Measure** → baseline CPU/memory, QPS, p95/p99 latency, saturation signals
✅ **Model** → understand bottlenecks, set SLO-based headroom, identify constraints (DB, cache, network, limits)
✅ **Scale** → right autoscaling strategy (HPA/VPA/Cluster Autoscaler/Karpenter), safe thresholds, load tests
✅ **Operate** → dashboards + alerts + regular review so growth doesn’t become incidents

Read here:
[https://www.cloudopsnow.in/capacity-planning-in-cloud-cpu-memory-qps-latency-scaling-the-engineer-friendly-playbook/](https://www.cloudopsnow.in/capacity-planning-in-cloud-cpu-memory-qps-latency-scaling-the-engineer-friendly-playbook/)

If you’re building or running systems in production and wondering why incidents still feel “invisible,” this article is ...
26/01/2026

If you’re building or running systems in production and wondering why incidents still feel “invisible,” this article is a clean, beginner-friendly Observability 101 guide that explains Logs vs Metrics vs Traces in plain English—and, more importantly, tells you what to instrument first so you get the fastest debugging wins without boiling the ocean.

Observability isn’t “add more dashboards.” It’s having the right signals when things break:

✅ Metrics → What’s wrong? (latency, errors, saturation, throughput)
✅ Logs → What happened? (events + context, structured logging)
✅ Traces → Where is it slow/broken? (end-to-end request path across services)

A solid order to start:

Golden Signals / RED metrics first

Add structured logs with correlation IDs

Instrument distributed tracing for critical flows

Read the full guide here:
https://www.cloudopsnow.in/observability-101-logs-vs-metrics-vs-traces-and-what-to-instrument-first/

If you’re managing multiple AWS accounts / Azure subscriptions / GCP projects, governance can quickly turn into chaos—di...
23/01/2026

If you’re managing multiple AWS accounts / Azure subscriptions / GCP projects, governance can quickly turn into chaos—different standards, inconsistent security, surprise bills, and “who changed what?” confusion. This guide shares a practical, step-by-step way to build scalable guardrails so teams can move fast without breaking compliance, security, or cost controls.

✅ What you’ll implement (real, scalable guardrails):

A clean org structure (accounts/projects grouped by env, team, workload)

Standard baselines for IAM, networking, logging, and monitoring

Policy-as-code guardrails (prevent risky configs before they land)

Cost guardrails (budgets, quotas, tagging rules, anomaly checks)

Automated onboarding (new account/project setup in minutes, not days)

Day-2 operations: drift detection, exception handling, and audit readiness

Read the full step-by-step guide here:
https://www.cloudopsnow.in/multi-account-multi-project-governance-guardrails-that-scale-practical-step-by-step/

If you’re setting up cloud audit logging (AWS/Azure/GCP) and feel overwhelmed by what to log, how long to retain it, and...
23/01/2026

If you’re setting up cloud audit logging (AWS/Azure/GCP) and feel overwhelmed by what to log, how long to retain it, and when to alert, this engineer-friendly guide breaks it down step-by-step with practical use cases—so you can improve security and troubleshooting without drowning in noisy logs.

Cloud Audit Logging — what actually matters:

✅ What to log (must-have)

IAM/auth changes, privileged actions, policy edits

Network/security changes (SG/NACL/firewall, public exposure)

Data access events (storage reads, DB admin actions)

Kubernetes + workload changes (deployments, secrets, config)

✅ Retention (simple rule of thumb)

Short-term “hot” logs for investigations + debugging

Longer retention for compliance + incident timelines

Archive strategy so costs don’t explode

✅ Alerting that’s useful (not noise)

Root/admin activity, unusual geo/logins

Permission escalations, key creation, MFA disabled

Sudden spike in denied actions or data downloads

Changes to logging itself (tampering / disable events)

Read the full step-by-step guide here:
https://www.cloudopsnow.in/cloud-audit-logging-what-to-log-retention-and-alerting-use-cases-engineer-friendly-step-by-step/

If you’re setting up Kubernetes access for teams and want it to be secure, least-privilege, and easy to maintain, this R...
22/01/2026

If you’re setting up Kubernetes access for teams and want it to be secure, least-privilege, and easy to maintain, this RBAC cookbook walks through ready-to-use role patterns for Dev, SRE, and Read-only users—plus the common mistakes that accidentally grant too much power.

Kubernetes RBAC gets messy fast unless you standardize it:

✅ Dev role → limited to a namespace (deploy, view logs, exec only if needed)
✅ SRE role → broader operational access (debug, scale, rollout, events) with guardrails
✅ Read-only role → safe observability access (get/list/watch) without mutation rights
✅ Best practices → avoid ClusterAdmin, prefer Role + RoleBinding, review permissions, and validate with kubectl auth can-i

Read the full cookbook here:
https://www.cloudopsnow.in/kubernetes-rbac-cookbook-common-roles-dev-sre-read-only-safely/

If you’re running containers in production (Kubernetes or not) and want security that actually works in real life—not ju...
21/01/2026

If you’re running containers in production (Kubernetes or not) and want security that actually works in real life—not just compliance checklists—this guide breaks container security into a practical, engineer-friendly system: image scanning, runtime policies, and least privilege, with clear steps you can apply immediately.

Container security isn’t one tool. It’s a workflow you run continuously:

✅ Image Scanning → catch vulnerable packages, secrets, and risky configs before deploy
✅ Runtime Policies → prevent suspicious behavior in production (unexpected processes, file access, network calls)
✅ Least Privilege → minimize blast radius (non-root, minimal capabilities, tight RBAC, restricted egress)

Read here:
https://www.cloudopsnow.in/container-security-done-right-image-scanning-runtime-policies-and-least-privilege/

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