POSTGRESQL CONSULTATIVE SUPPORT · 24×7×365
Full-Stack PostgreSQL Consultative Support, Operated by Senior Practitioners
MinervaDB delivers 24×7×365 consultative support for mission-critical PostgreSQL — performance engineering, high-availability operations, security hardening, and incident response staffed entirely by senior PostgreSQL engineers, not ticket triage agents. One contract covers community PostgreSQL, EDB Postgres Advanced Server, Crunchy, Percona Distribution, Aurora, RDS, Cloud SQL, and Azure Database for PostgreSQL.
<15 min
P1 incident response — global follow-the-sun
99.99%
Uptime engineering target on managed PostgreSQL
PG 12–18
Every supported version, every major extension
24×7×365
Senior PostgreSQL engineers on-call always
Engineering teams across FinTech, SaaS, e-commerce, AdTech, healthcare, gaming, and digital advertising rely on MinervaDB for mission-critical PostgreSQL operations — incident response measured in minutes, performance engineering measured in milliseconds, and architecture decisions made by practitioners who have run PostgreSQL at scale.
WHY CONSULTATIVE SUPPORT
Break-Fix Support Cannot Run a Mission-Critical Postgres Estate
Most PostgreSQL support contracts are written for a world that no longer exists. The ticket arrives, a level-one agent runs through a script, a level-two engineer is summoned, and three escalation steps later somebody who actually understands PostgreSQL internals reads the EXPLAIN output. By the time the root cause is identified, the incident has already cost the business an hour of revenue, a reputation tax with the customer, and a board-level question about why the database team needed half a day to read a query plan.
MinervaDB engineers PostgreSQL support the way we engineer everything else — built around senior practitioners, structured for fast root-cause analysis, and operated against measurable service-level commitments. Every engineer on the rotation has worked PostgreSQL incidents at production scale, every escalation goes straight to a person who can read the source code, and every engagement is staffed by humans who own the outcome from the first page to the post-incident review.
We work with engineering organizations at three operating points: teams running self-managed PostgreSQL clusters that need a senior partner on retainer, teams running managed PostgreSQL on Amazon Aurora, Amazon RDS, Google Cloud SQL, or Azure Database for PostgreSQL that need expertise the cloud provider does not deliver, and teams running mixed estates where consultative support has to follow workloads across self-managed and managed environments without seams in coverage.
FIVE POSTGRESQL SUPPORT PILLARS
The Five Engineering Outcomes Every Support Engagement Delivers
Every PostgreSQL support contract is engineered around the five pillars that define a mission-critical database practice. Each pillar has measurable SLOs, named senior engineers, and a documented operating cadence — no part of the work is parked behind generic ticket queues.
Performance
Query-level engineering on every incident — pg_stat_statements, auto_explain, autovacuum tuning, indexing strategy, and execution-plan analysis run by engineers who can read the planner source code and explain why a hash join lost to a nested loop on a specific workload.
Scalability
Capacity engineering grounded in workload telemetry — partitioning strategy, connection-pool architecture with PgBouncer and Pgpool, read-replica fan-out, sharding patterns with Citus, and the kind of write-path engineering that keeps OLTP latency flat as traffic grows.
High Availability
Streaming and logical replication engineered to RPO and RTO commitments, Patroni and pg_auto_failover orchestration, multi-region disaster recovery, and the automated failover testing that proves the architecture works before the outage that requires it.
Database Reliability Engineering
Observability, runbooks, on-call rotations, blameless post-incident reviews, capacity reforecasts, and the operational discipline that turns PostgreSQL from a black box into a measurable, ownable engineering system — not an inherited risk.
Data Security
Authentication architecture, encryption at rest and in transit, role-based access design, row-level security, audit logging, and compliance engineering calibrated for GDPR, HIPAA, SOX, PCI DSS, and SOC 2 — security as a property of the cluster, not a quarterly remediation.
SUPPORT TIER MATRIX
Three Tiers Calibrated to the Cost of Downtime
Every PostgreSQL workload sits somewhere on the downtime-cost curve, and the support tier is engineered to match. Standard covers the long tail of important-but-not-revenue-critical clusters, Enterprise covers production workloads, and Mission-Critical engineers the platform for environments where a 30-minute outage is a board-reportable event.
SEVEN CORE SUPPORT SERVICES
Seven Engineering Practices That Make Up the Complete Support Engagement
PostgreSQL Consultative Support for Tailored Solutions
Every support contract gives the engineering organization access to all seven practices. Most workloads draw on three or four in any given quarter — incident response and performance engineering by default, with HA work, upgrades, security audits, or capacity planning sequenced around the workload calendar.
24×7 Incident Response Engineering
Senior PostgreSQL engineers on-call across every time zone, with P1 response measured in minutes — not callback windows. Every incident is owned end to end from first page through root-cause analysis, fix deployment, and post-incident review. No escalation tiers between the customer and the engineer who can read the planner source. Runbooks document the exact diagnostic steps for the top failure modes — replication lag spikes, autovacuum runaway, connection saturation, lock contention, WAL accumulation — so resolution time does not depend on which engineer answers the page.
PostgreSQL Performance Engineering
Query-level engineering using pg_stat_statements, auto_explain, pg_buffercache, pg_stat_io, and the full planner instrumentation. Index-strategy reviews that consider B-tree, BRIN, GIN, GiST, hash, and partial indexes against the actual workload mix. Configuration tuning across shared_buffers, work_mem, effective_cache_size, max_wal_size, checkpoint_timeout, and the autovacuum parameters that determine whether OLTP latency stays flat under sustained write load. Outcomes are benchmarked before and after with reproducible workload replays.
High Availability & Disaster Recovery
Streaming and logical replication architectures engineered to defined RPO and RTO targets. Patroni and pg_auto_failover orchestration designed for the operational reality of the engineering organization — not a vendor whitepaper. Multi-region disaster recovery with pgBackRest, WAL-G, or Barman for point-in-time recovery. Quarterly failover drills with documented results, because a failover plan that has not been tested in production conditions is a failover hope, not a failover plan.
PostgreSQL Upgrades & Migrations
Major version upgrades planned, tested, and executed with zero or minimal downtime — logical-replication cutover, pg_upgrade with rehearsed rollback, and dual-write transition patterns where the workload demands it. Migrations from Oracle, SQL Server, MySQL, MariaDB, MongoDB, and DynamoDB scoped, tested, and executed with workload-replay validation. Schema, query, and stored-procedure conversion handled with ora2pg, pgloader, custom tooling, and senior engineering judgment.
Security & Compliance Engineering
Authentication architecture across SCRAM-SHA-256, LDAP, Kerberos, certificate-based authentication, and IAM integration on managed PostgreSQL. Encryption at rest with TDE-equivalent patterns, in-transit via TLS, and column-level encryption where the threat model demands it. Row-level security policies engineered against the actual access patterns. Audit logging with pgaudit, integrated with the SIEM. Compliance posture calibrated for GDPR, HIPAA, SOX, PCI DSS, and SOC 2 with documented evidence trails.
Capacity Planning & Workload Engineering
Workload telemetry collection and analysis — pg_stat_statements baselines, throughput and latency profiles, growth-curve modeling, and capacity reforecasts every quarter. Partitioning strategy designed against actual access patterns. Connection-pool architecture with PgBouncer in transaction-pooling mode, Pgpool for read-write splitting, and pgcat where the workload calls for it. Read-replica fan-out and Citus sharding evaluated against the long-term workload trajectory, not the current quarter.
Architecture Reviews & Engineering Audits
Independent architecture reviews of the PostgreSQL estate — cluster topology, replication design, backup posture, observability coverage, security configuration, and operational runbooks audited against the senior PostgreSQL engineering practices the broader community has converged on. Findings are written up as actionable engineering tickets the in-house team can execute, with prioritization tied to operational risk and business impact. Quarterly reviews keep the architecture aligned with workload evolution.
DEEP DIVE · INCIDENT RESPONSE ENGINEERING
Incident Response Engineered for the First Page, Not the Third Escalation
The hardest minutes of any production database incident are the first ten — when the alerting platform is reporting latency spikes, the application team is asking what is happening, the executive sponsor is on Slack, and the engineer on call has roughly six hundred seconds to figure out whether the problem is replication lag, autovacuum, a lock storm, a runaway query, or something more interesting. The quality of the next four hours is decided in those ten minutes, and the quality of those ten minutes is decided by who answers the page.
MinervaDB structures incident response so the engineer who answers the page is a senior PostgreSQL practitioner — not a level-one agent gating access to expertise. Every on-call rotation is staffed by engineers who have run PostgreSQL clusters in production at scale, debugged planner regressions across major version upgrades, designed Patroni clusters that survived real datacenter failures, and written post-incident reports that satisfied real auditors. There is no escalation ladder between the customer and that engineering depth.
Every incident follows the same engineering discipline. The on-call engineer acknowledges within the SLA window and joins the incident channel. Triage runs against documented runbooks — replication lag, vacuum-wraparound risk, connection saturation, WAL accumulation, autovacuum stalls, lock contention, planner regression, network partitions, storage saturation. Diagnostic data is collected with the same toolchain used by the broader PostgreSQL engineering community — pg_stat_activity, pg_locks, pg_stat_progress_vacuum, pg_stat_replication, pg_stat_wal, pg_stat_io. The fix is engineered, tested where possible, and deployed. The post-incident review is written within two business days, captured in a permanent knowledge base, and used to harden the runbook for the next iteration.
The operational result is predictable. Engineering organizations that move from generic break-fix support to MinervaDB consultative support typically see P1 mean-time-to-acknowledge drop into the single-digit-minutes range, mean-time-to-resolution drop by half or more on the top recurring failure modes, and the volume of repeat incidents fall by 40 to 60 percent within two quarters as the runbook library matures. The on-call experience for the in-house engineering team improves in parallel — incidents that used to wake up the database lead now resolve inside the support engagement, with a written record the team reviews the next morning rather than fights through at 3 AM.
DEEP DIVE · PERFORMANCE & QUERY ENGINEERING
Postgres Performance, Engineered Down to the Query Plan
PostgreSQL performance is not a configuration problem. It is a query-engineering problem with a configuration tax — a planner that makes intelligent decisions when the statistics are correct, the indexes are right, the autovacuum cadence keeps the visibility map current, and the workload fits the buffer pool. When any of those assumptions breaks, the planner makes intelligent decisions about the wrong reality, and the queries that used to run in milliseconds start scanning hundreds of millions of rows for no reason the application team can explain.
MinervaDB performance engineering starts where the planner does — with the data. Every performance engagement opens with a pg_stat_statements baseline that captures the actual workload mix, the queries that dominate buffer-cache pressure, the queries that drive write amplification, and the queries with the highest planner cost-to-actual-cost ratio. From there, EXPLAIN ANALYZE on the worst offenders, auto_explain configured on the production cluster with sample sampling, pg_stat_io correlated against shared_buffers utilization, and the kind of execution-plan inspection that separates a senior PostgreSQL engineer from a generalist DBA.
The configuration layer is engineered to match. shared_buffers, work_mem, effective_cache_size, maintenance_work_mem, and the autovacuum parameters are tuned against the workload telemetry — not against the default values inherited from the installer or the recommendations from a five-year-old blog post. random_page_cost is set to match the storage tier the cluster actually runs on. The planner cost constants are reviewed against the cardinality estimates the planner is producing, and the statistics targets are raised on the columns where the join selectivity estimates are driving bad plans. Every change is rolled out behind a workload replay, benchmarked against the baseline, and signed off by the in-house engineering team before it lands in production.
Indexing strategy is engineered around the workload pattern — not bolted on after the slow-query report arrives. B-tree indexes for selective predicates and ordered scans, BRIN for huge append-only ranges where the natural data clustering is preserved, GIN and GiST for full-text and geospatial workloads, and partial and expression indexes for the workload-specific patterns that generic indexing strategies miss. Every recommended index is benchmarked for write-amplification cost, evaluated against the planner choices, and validated to actually be picked up by the queries that justified creating it. The deliverable is a measurable improvement in p95 and p99 latency, captured in the workload baseline and reviewed against the application SLO every quarter.
DEEP DIVE · HIGH AVAILABILITY, DR & REPLICATION
High Availability Engineered to Survive the Failure That Actually Happens
Most PostgreSQL HA architectures are designed for the failure modes the architect read about. Production failures are different — a NIC starts flapping at 2 AM, a storage volume develops a slow-burn latency regression, a streaming replica drifts ten minutes behind under a vacuum spike, the network partition between availability zones lasts long enough for split-brain detection to misfire. The HA architecture either survives the failure that actually occurs or it produces a postmortem that explains why a four-nines target ended the quarter at three nines.
MinervaDB engineers PostgreSQL HA against the failure catalogue we have actually seen in production — across more than a decade of incidents — not the textbook taxonomy. Streaming replication is configured with synchronous_commit, synchronous_standby_names, and wal_keep_size sized to the actual write-rate profile of the workload. Patroni and pg_auto_failover are deployed with consensus-store topology that survives a single-zone failure, and the leader election timeouts are calibrated against the latency profile of the etcd or Consul cluster actually running underneath. Logical replication is engineered for the cross-version upgrade, multi-region read-fanout, and selective table-level data movement use cases where streaming replication is the wrong tool.
Disaster recovery is a separate engineering discipline. pgBackRest, WAL-G, and Barman are configured for compressed, encrypted, parallelized backups with point-in-time recovery validated quarterly against the production data volume. Backup-restore drills are run on a defined cadence, the restore times are measured and tracked, and the recovery runbook is updated against every drill so the engineering team that has to execute it under pressure has a procedure that actually reflects the production environment. Cross-region replicas are kept warm with WAL streaming, and the failover criteria are documented as boolean conditions — not subjective judgement calls — so the runbook can be executed by any senior engineer on the rotation, not just the one who designed the architecture.
The HA architecture is proved against the workload it actually has to protect. Quarterly failover drills are mandatory, results are written up, and the RPO and RTO numbers in the support contract are measured against real drill data — not vendor brochures. Engineering organizations that move from a paper HA architecture to a MinervaDB-engineered HA architecture typically see the difference the first time a production failure occurs and the cluster fails over within the documented RTO without an incident bridge that lasts longer than the failover itself. That is the operating result the support contract is structured to produce, and the architecture is engineered against.
POSTGRESQL COVERAGE MATRIX
Every PostgreSQL Version, Every Extension, Every Cloud — Under One Contract
Vendor neutrality means engineering across the full PostgreSQL ecosystem — community releases, enterprise distributions, managed cloud variants, and the orchestration, replication, and observability tooling that surrounds production deployments. One support contract covers the entire estate.
For ClickHouse-based analytics workloads that sit alongside PostgreSQL OLTP, our partner ChistaDATA delivers 24×7 consultative support and managed services as part of the MinervaDB engineering practice.
INDUSTRIES WE SUPPORT
PostgreSQL Support Calibrated to the Workload, Not the Industry Brochure
Production PostgreSQL workloads look different across industries — a payments OLTP cluster has nothing in common with a clinical-data warehouse, and a leaderboard write path has nothing in common with a SaaS multi-tenant control plane. MinervaDB engineers PostgreSQL support calibrated to the workload pattern, the regulatory perimeter, and the engineering culture that operates the platform every day.
FinTech & Payments
Mission-critical OLTP, exactly-once processing patterns, regulated audit logging, and PCI DSS-aligned PostgreSQL infrastructure engineered for institutions where database availability is a board-level metric.
SaaS & Platform Engineering
Multi-tenant PostgreSQL architectures, row-level security at scale, blue-green deployment patterns, and the operational discipline that keeps a million-tenant database fleet shipping new features every week.
E-Commerce & Retail
Peak-season write-path engineering, catalog-search indexing with PostgreSQL full-text and pgvector, recommendation-feature workloads, and OLTP performance engineered for traffic spikes measured in orders of magnitude.
AdTech & Marketing
High-throughput event ingest, attribution-graph workloads, low-latency lookup tables with PgBouncer fan-out, and the kind of write-path tuning that keeps p99 latency flat under sustained workload pressure.
Healthcare & Life Sciences
HIPAA-aligned PostgreSQL deployments, audit logging with pgaudit, encryption architecture, role-based access engineered against the actual clinical-data access patterns, and the governance posture that survives a regulator visit.
Gaming & Digital Media
Leaderboard data structures, player-state OLTP, event-stream ingestion patterns, and PostgreSQL clusters engineered for the spiky workload profile that gaming and streaming-media platforms produce as a matter of course.
ENGAGEMENT MODEL
Transparent Contracts, Strict Operational Commitments
Support contracts are structured around the operational reality of running PostgreSQL — not vendor packaging. Senior engineers are the default staffing model, escalation paths are documented, and every commitment in the contract is measurable against the operational scorecard the engineering team reviews every month.
FREQUENTLY ASKED QUESTIONS
Questions Engineering Leaders Ask Before a PostgreSQL Support Contract
If the question is not covered below, a 30-minute conversation with a senior MinervaDB PostgreSQL engineer is the fastest way to scope the contract — no qualifying call, no sales triage.
What exactly does MinervaDB consultative PostgreSQL support cover?
Consultative support covers the full operational lifecycle of a PostgreSQL estate — 24×7 incident response, performance engineering, high-availability and disaster-recovery architecture, security and compliance engineering, upgrades and migrations, capacity planning, and quarterly architecture reviews. One contract covers community PostgreSQL plus enterprise distributions and managed cloud variants. The work is done by senior PostgreSQL engineers, not first-line ticket triage.
How is MinervaDB support different from EnterpriseDB, Percona, or Crunchy?
MinervaDB is vendor-neutral by design — no resale agreements, no preferred distribution, no incentive to recommend one PostgreSQL variant over another. Every engineer on the rotation is a senior PostgreSQL practitioner, and the contract bills against measurable engineering work — not per-instance licensing or per-seat packaging. Customers stay on community PostgreSQL, EDB, Percona, Crunchy, or a managed cloud variant, and MinervaDB engineers across the entire estate without a vendor lens.
What is the P1 incident response SLA?
P1 response is 15 minutes on the Mission-Critical tier, 30 minutes on Enterprise, and 60 minutes on Standard — measured from the moment the page is acknowledged in the ticket portal or escalation channel. The on-call rotation is staffed by senior PostgreSQL engineers across global time zones, so every P1 page is answered by a practitioner who can read the planner output and the source code, not a level-one agent waiting to escalate.
Does MinervaDB support managed PostgreSQL on AWS, GCP, and Azure?
Yes — Amazon RDS for PostgreSQL, Amazon Aurora PostgreSQL, Google Cloud SQL for PostgreSQL, AlloyDB, Azure Database for PostgreSQL Flexible Server, and Azure Cosmos DB for PostgreSQL are all covered under the same support contract. Engineering covers the operational layer the cloud provider does not — query engineering, indexing strategy, schema design, partitioning, replication topology, capacity planning, and the security and compliance posture that managed-service consoles do not engineer for the workload.
Can MinervaDB take over operations from an existing in-house DBA team?
Yes — MinervaDB engagements range from senior-engineer-on-retainer working alongside an in-house team, to fully outsourced 24×7 operations where MinervaDB carries the on-call rotation, performance engineering, HA design, and architecture roadmap. Most engagements start as collaborative and evolve as the in-house team’s needs change. A documented handover at the end of every engagement ensures no part of the operating knowledge is locked inside the support contract.
What PostgreSQL versions does MinervaDB support?
Every supported community PostgreSQL major version — currently 12, 13, 14, 15, 16, and 17 — plus the matching versions across EDB Postgres Advanced Server, Crunchy Certified PostgreSQL, and Percona Distribution for PostgreSQL. End-of-life version support is available as a separate engagement scoped against the operational risk profile, with a documented migration roadmap to a supported version.
How does the onboarding process work?
Onboarding is a two-week engineering sprint. Week one covers cluster inventory, replication and backup topology, observability coverage, and security and compliance posture. Week two covers a baseline performance audit, a runbook review, an escalation-path setup, and a written onboarding report that documents the operational starting position. After week two, the support contract is live and the engineering rotation owns the operational scorecard.
Which compliance frameworks does the support engagement support?
GDPR, HIPAA, SOX, PCI DSS, and SOC 2 — every PostgreSQL cluster under support is engineered with audit logging via pgaudit, role-based access control, encryption at rest and in transit, retention policies, vulnerability assessment, and a documented incident-response procedure. Evidence trails are produced as part of the operating practice, so the next audit cycle does not become a separate engineering project.
The right way to support a mission-critical PostgreSQL cluster is to make sure the engineer who answers the page at 3 AM has already designed clusters like the one on fire — has read the planner source, has debugged the autovacuum behaviour, has executed the failover drill. Consultative support is not a ticket queue. It is senior engineering, on call, accountable for the operational scorecard. That is the practice MinervaDB ships, every contract.
Shiv Iyer — Founder & CEO, MinervaDB
READY FOR SENIOR POSTGRESQL ENGINEERING ON CALL
Let’s Engineer the Support Operation This Postgres Estate Deserves
A 30-minute conversation with a senior MinervaDB PostgreSQL engineer is enough to scope the right support tier, define the onboarding sprint, and document the operational starting position. No qualifying call, no sales funnel — just engineering.
Sales: +1 (844) 588-7287 (USA) · +1 (415) 212-6625 (USA) ·
Support: support@minervadb.com · Remote DBA: remotedba@minervadb.com