Anirudh Sridharan (Ani)
Hi, I'm Ani
Engineering leader with deep experience guiding teams and shipping resilient platforms from startups to enterprise scale. Delivering 99.999% reliability through battle tested practices, smart automation, and relentless optimization for Fortune 500 enterprises and hyper growth startups alike. AI-native engineering leader building autonomous, self-healing systems that eliminate toil and scale reliability through intelligent automation.
Beyond the Code
When I'm not architecting systems, I'm chasing horizons. in one of the 48 states often by backroads, camera in hand, exploring trails, and sampling craft beers. The road teaches patience, perspective, and the value of the scenic route.
Ask me about cloud, AI, road adventures, or how to make complex systems feel effortless.
Engineering Leadership
Built high performing teams from scratch and scaled multi team initiatives across infrastructure operations, observability, and systems reliability.
Hands-on Engineer
Designing and shipping infrastructure as code, Kubernetes platforms, and backend services; debugging production systems.
Thought Leadership
Practicing customer obsessed engineering, using real user journeys to shape reliability, CX, and operational guardrails.
Platform Engineering
Architecting and building scalable internal developer platforms with golden paths, self service infrastructure, and CI/CD at scale.
Systems Reliability & Operations
Defining SLIs/SLOs, capacity planning, and chaos/performance testing to make quiet oncall a first class outcome.
Operations & Incident Management
Leading incident command, tuning escalation policies, and using correlationID tracing to accelerate root cause analysis.
Reliability at Scale
Delivering multi region architectures and high throughput telemetry pipelines with four nines availability targets.
AI-Native Operations
Leading teams in building production grade AI agents for reliability workflows, MCP servers for observability platforms, and LLM powered incident analysis that turns tribal knowledge into instant insights.
AI-First Observability
Using LLMs and ML models to correlate signals across millions of metrics, traces, and logs to surface the few things that actually matter.
Autonomous Remediation
Building self-healing automation that resolves 70%+ of recurring incidents safely and consistently.
Intelligent Capacity Planning
Forecasting demand and tuning capacity with ML-driven models to reduce waste while protecting availability.
ChatOps & AI Agents
Context-aware assistants that reduce MTTR by 50%+ via automated triage, summaries, and runbook execution.
Tech I Get My Hands Dirty With
The platforms and tools I actually use, not just talk about.
- Build AI features that support operations (summaries, triage, routing, and knowledge retrieval).
- Run evaluation harnesses to keep quality stable as prompts/models/tools evolve.
- Ship AI into real workflows with observability, safety, and rollback paths.
- Evaluation-first: golden datasets, regression checks, release gates.
- Prompt/config as code: versioned, reviewed, tested, and deployed via CI.
- Guardrails + telemetry: quality, latency, safety, and drift monitoring.
- Production AI launches with measurable quality targets and release gates.
- Lower regression risk during model/prompt/tool changes through automated gating.
- Predictable runtime behavior via safety controls and operational visibility.
References
What colleagues and managers say!
Interactive Tools
25+ diagnostics, converters & calculators
Latest Insights
Experiments, playbooks & 2AM thoughts