I keep production boring.Even at 3 AM.
I'm Shivam, a platform and SRE engineer in Bengaluru. Seven years of building the platforms, autoscaling and access systems that let teams ship without getting paged, and writing up what broke.
Currently Member of Technical Staff, SRE at Flexera
- Kubernetes
- AWS
- Terraform
- Argo CD
- KEDA
- Karpenter
- Graviton
- Flink
- Airflow
- Kafka
- Strimzi
- VictoriaMetrics
- Prometheus
- Grafana
- Loki
- Vector
- Go
- Python
- eBPF
- Azure
What I build
Infrastructure that behaves the same at 3 PM and 3 AM. These are the systems I keep coming back to.
Rate limiting at the edge of every service
- Problem:
- Bursty internal API traffic could exhaust shared capacity.
- Contribution:
- Put per-tenant quotas in Envoy with a shared rate-limit service and Redis counters.
- Outcome:
- A 100-requests-per-hour test quota admitted exactly 100 requests.
Quota behavior
Illustrative browser demo. Requests do not reach Envoy or Redis.
- tenant-a (default)0 / 5 per s
- tenant-b (premium)0 / 50 per s
- tenant-c (default)0 / 5 per s
- Last burst
- none yet
- Allowed
- 0
- Rate limited
- 0
Platforms with paved paths
- Problem:
- Data teams needed repeatable operations for streaming and scheduled jobs.
- Contribution:
- Built self-service Flink and Airflow platforms on Kubernetes.
- Outcome:
- Airflow platform work reduced operational effort by 50%.
Access that expires
- Problem:
- Production exec access needed a narrow scope and a hard end time.
- Contribution:
- Built approved, namespace-scoped access with scheduled expiry and failure-safe cleanup.
- Outcome:
- Access expires without a person having to remember to revoke it.
A data lake without the small-files tax
- Problem:
- Tenant path partitioning multiplied small objects and query overhead.
- Contribution:
- Wrote Parquet by Kafka partition, then compacted into query-oriented tables.
- Outcome:
- Object counts fell about 120× on the busiest stream and over 1,000× on two others.
Metrics you can afford
- Problem:
- Monitoring cost was growing with a large Kubernetes and EC2 estate.
- Contribution:
- Moved to VictoriaMetrics and added cardinality controls across ingest and query paths.
- Outcome:
- Monitoring infrastructure cost fell 60%.
Logs as a pipeline, not a pile
- Problem:
- Node-local logs needed durable delivery and replayable parse failures.
- Contribution:
- Built a Vector and Kafka pipeline with buffered S3 sinks and dead-letter routing.
- Outcome:
- Aggregator outages become Kafka lag; parse failures remain available for replay.
Receipts, not adjectives
The before and after of the work, as an engineer would report it. Costs went down, toil went down, and access stopped being permanent.
Full case studies$
Seven years, one trace
My career drawn as a distributed trace. Companies are spans, roles are child spans, projects sit underneath. Expand one.
Flexera
Member of Technical Staff, SRE
Reliability for multi-region SaaS on Kubernetes and AWS: autoscaling, storage, GitOps at fleet scale, and secure operator access.
- Event-driven autoscaling across regions
- Storage and delivery reliability on EKS
- Time-boxed production access
- Start
- Apr 2024
- End
- Still running
- Duration
- 2y 7mo
- Where
- Bengaluru
- Stack
- EKS, KEDA, Argo CD, Lambda, CloudFormation
Select a span to inspect it. Arrow keys move between spans; right and left expand or collapse them.
The 3 AM Brew
Incident notes and design write-ups, brewed after the pager goes quiet.