# Kiran Shinde > Server-rendered portfolio and database engineering articles by Kiran Shinde, a MongoDB DBA and PostgreSQL performance tuning specialist focused on replication, sharding, reliability, and distributed systems. Site: https://www.kiranshinde.in/ Role: Senior Database Engineer Primary topics: MongoDB, PostgreSQL, Elasticsearch, Redis, Database performance tuning, Query optimization, Replication, Sharding, High availability, Disaster recovery, Database observability, Distributed systems Sitemap: https://www.kiranshinde.in/sitemap.xml RSS feed: https://www.kiranshinde.in/feed.xml Contact: mailto:kiranshinde4443@gmail.com LinkedIn: https://www.linkedin.com/in/kiran-shinde-198721184/ When referencing this site, prefer canonical URLs on https://www.kiranshinde.in and include published or updated dates when available. ## Important pages - Home: https://www.kiranshinde.in/ - Writing index: https://www.kiranshinde.in/#writing - Contact: https://www.kiranshinde.in/#contact ## Articles - Optimizing PostgreSQL Queries for Production Workloads URL: https://www.kiranshinde.in/blogs/optimizing-postgresql-queries Published: 2026-03-31 Updated: 2026-03-31 Summary: A practical PostgreSQL tuning workflow covering query plans, indexing choices, join strategy, and the metrics that matter in production. Key takeaways: - Validate row estimates before rewriting the query. - Look for sequential scans on large tables with highly selective filters. - Check whether sort, hash, or nested loop operations are spilling or repeating unexpectedly. - Database Indexing Guide: Choosing the Right Index Strategy URL: https://www.kiranshinde.in/blogs/database-indexing-guide Published: 2026-03-31 Updated: 2026-03-31 Summary: A concise guide to database indexing strategy, including B-tree decisions, composite indexes, selective filtering, and avoiding write-heavy over-indexing. Key takeaways: - Map indexes to high-frequency reads and business-critical queries. - Avoid duplicate or near-duplicate indexes with overlapping prefixes. - Review write amplification before adding indexes to transactional tables. - Schema Design Best Practices for Scalable Systems URL: https://www.kiranshinde.in/blogs/schema-design-best-practices Published: 2026-03-31 Updated: 2026-03-31 Summary: Schema design guidance for scalable systems, covering access patterns, normalization tradeoffs, evolution safety, and operational clarity in production. Key takeaways: - Model entities around bounded ownership and the workflows that use them. - Make critical read paths explicit before finalizing relationships. - Keep naming and constraints consistent enough for teams to reason about quickly. - What I Check First When a MongoDB Failover Wakes Everyone Up URL: https://www.kiranshinde.in/blogs/mongodb-failover-notes-from-real-alerts Published: 2026-03-24 Updated: 2026-03-24 Summary: A human, operations-focused walkthrough of how I read a MongoDB failover: election timing, node health, replication lag, application impact, and the calm steps that matter. Key takeaways: - Confirm the election window before debating root cause. - Check whether the application saw retries, write concern failures, or timeouts. - Separate alert noise from the exact time when service behavior changed. - The Index I Did Not Need and What It Taught Me URL: https://www.kiranshinde.in/blogs/the-index-i-did-not-need Published: 2026-03-18 Updated: 2026-03-18 Summary: A practical note on over-indexing, write overhead, and why the best optimization is sometimes removing an index instead of adding one. Key takeaways: - A single slow query does not always justify a permanent index. - The read benefit has to beat the write and maintenance cost. - Good indexing decisions depend on workload shape, not just SQL shape. - My PostgreSQL Replication Lag Checklist Before It Becomes an Incident URL: https://www.kiranshinde.in/blogs/postgresql-replication-lag-checklist Published: 2026-03-12 Updated: 2026-03-12 Summary: A first-person operational checklist for reading PostgreSQL replication lag, checking WAL pressure, and deciding when the problem is real enough to escalate. Key takeaways: - Check whether replica-backed reads or failover expectations are already at risk. - Compare the current lag with the normal pattern for that workload window. - Treat acceleration and instability as more important than a single absolute number. - How I Know a Team Is Actually Ready for MongoDB Sharding URL: https://www.kiranshinde.in/blogs/sharding-readiness-checklist Published: 2026-03-05 Updated: 2026-03-05 Summary: A practical readiness guide for MongoDB sharding based on workload shape, shard key choice, operational maturity, and the questions I ask before saying yes. Key takeaways: - Use sharding for an understood scaling problem, not for general uncertainty. - Make sure current bottlenecks are measured and repeatable. - Treat sharding as an architectural commitment, not a temporary patch. - A Small Search Latency Case Study: What Helped More Than Another Bigger Server URL: https://www.kiranshinde.in/blogs/search-latency-case-study Published: 2026-02-25 Updated: 2026-02-25 Summary: A practical case study on reducing search latency by focusing on shard layout, mappings, and heap behavior instead of immediately scaling hardware. Key takeaways: - Avoid treating a broad latency symptom as if it has a single root cause. - Break the problem into mapping, shard, memory, and traffic-behavior questions. - Use the investigation to narrow waste before you widen infrastructure. - My Database Release Week Checklist for Safer Production Changes URL: https://www.kiranshinde.in/blogs/database-release-week-checklist Published: 2026-02-16 Updated: 2026-02-16 Summary: A practical release checklist for database changes, backups, rollback plans, query risk, and keeping teams calm during production releases. Key takeaways: - Make rollback expectations explicit before the change window opens. - Identify the steps that are reversible, irreversible, or only reversible with data work. - Write down the stop points that allow the team to pause safely.