Database Reliability Engineering · since 2021
Database reliability engineering for production systems.
A cross-trained DBRE crew for managed operations, performance tuning, cost control, upgrades, and incident response across MySQL, PostgreSQL, MongoDB, and other production database systems. Managed-service availability and response commitments are defined by plan.
A focused assessment to review priorities, risks, and next steps. If a deeper technical audit would help, we'll define its access requirements, checks, and deliverables with you.
MySQL
8.0 · InnoDB
0.00k
queries/sec
PostgreSQL
16 · streaming repl
8ms
p99 latency
MongoDB
7.0 · 3-node RS
0
ops/sec
Valkey
8 · cluster
98.5%
cache hit rate
SQL Server
2022 · Always On AG
0.0k
instance IOPS
Sample Query Throughput
0.00k QPS[OK] pg_repl: replica synchronized (lag 0ms)
[OK] valkey: 99.4% hit rate — 0 evictions
[INF] mysql: buffer pool resized → 24G
[OK] mongo: shard balancer idle, chunks even
Interactive demonstration using sample data · not live customer telemetry
Teams we've worked with
Engineering teams trust us with production databases.
1,000+
Production Instances Supported
30+
Engineering Teams Served
14
Database Engines Supported
2021
Founded
Extend your in-house database team
One DBA shouldn't have to carry production alone.
Managed cloud databases automate much of the infrastructure layer, but your team still owns query performance, capacity, cost, and incident decisions. JusDB can add cross-trained DBRE capacity, with extended coverage available on qualifying managed-service plans when production needs it.
14
Database engines
relational, NoSQL, search, cache, and analytics systems
24/7
Managed coverage
available for production operations and escalation
15 min
P1 response target
available on qualifying managed-service plans
99.99%
Uptime target available
up to 99.99%; plan-specific scope and terms defined in your agreement
Relying on one specialist
- Deep production context concentrated with one person
- Coverage gaps during leave, handoffs, and simultaneous incidents
- Limited capacity across projects, incidents, and preventive work
- Runbooks and peer review compete with urgent production priorities
A strong DBA can transform a system, but production resilience should not depend on one person's availability.
A JusDB crew
- Cross-trained DBREs with shared context for your production systems
- Plan-based on-call coverage with documented handoffs
- Capacity for incident response, planned work, and prevention
- Response targets documented by severity in qualifying plans
The JusDB Difference
Database specialists for the systems your business depends on.
Database reliability engineering is our core, with experience across production estates spanning relational, NoSQL, search, caching, and analytics systems.
Make Database Spend Explainable
We baseline compute, storage, I/O, and licensing before recommending right-sizing or commitment changes. Every savings estimate states its assumptions and can be checked against your bill.
Measure Performance Changes
We profile query plans, waits, cache behavior, indexes, and connection pools, then validate changes against an agreed baseline instead of promising a universal speedup.
Plan-Backed Service Levels
Coverage hours, severity definitions, response and availability targets, exclusions, measurement, and service credits are documented in the selected plan and agreement.
A Team Around Your Team
Your in-house DBA keeps vital context and ownership. JusDB adds cross-trained engineers, documented handoffs, peer review, and 24/7 managed coverage when the selected plan includes it.
SRE Discipline, Not Firefighting
For managed SRE engagements, we define SLOs, track error budgets, run blameless postmortems, and automate toil using tooling suited to your environment, including Prometheus and Grafana.
Fast Escalation When It Matters
Qualifying managed-service plans define a P1 acknowledgement and escalation target. Response is measured separately from mitigation and resolution time.
Database reliability engineering is our core. Our cloud, FinOps, SRE, and automation work stays focused on production data systems.
Selected customer outcomes
Measured results from defined workloads and production events.
Each anonymized example states its measured scope, production event, or delivered capability. These are selected engagement results, not guaranteed or typical outcomes; results vary by environment and scope.
62% lower monthly spend
Anonymized Amazon RDS MySQL engagement
Monthly bill · $8,400 baseline → $3,200 after
How
Moved db.r5.4xlarge workloads to db.r6g.2xlarge and optimized queries; CPU fell from 85% to 28% in this selected workload.
Query p99: 4.2s → 180ms
Anonymized fleet-tracking engagement
Selected PostgreSQL hot path · p99 latency
How
Rewrote the hot query path, added covering indexes, cached read-heavy lookups in Valkey.
Multi-region failover delivered
Anonymized cross-border banking engagement
PostgreSQL + MongoDB + Valkey · multi-cloud
How
Configured failover, automated backups, monitoring, and alerting around the customer's recovery plan.
No database outage during the sale event
Anonymized flash-sale engagement
MySQL + Elasticsearch · recorded 10× peak-traffic event
How
Pre-scaled read replicas, load-tested the checkout path, and tuned connection pooling for the traffic spike.
No recorded cutover downtime
Anonymized multi-tenant SaaS engagement
PostgreSQL 14 → 16 · planned production cutover
How
Used logical replication to a new major version, then completed a controlled application cutover.
Selected queries completed 3× faster
Anonymized patient-data platform engagement
PostgreSQL + TimescaleDB · selected time-series queries
How
Partitioned time-series data with TimescaleDB hypertables and added audit logging for the customer’s healthcare-data requirements.
Illustrative P1 response
A defined incident path from alert to acknowledgement, recovery, and review.
This is an illustrative workflow, not a live incident or a promised resolution timeline. A 15-minute P1 acknowledgement target is available on qualifying managed-service plans; actual mitigation and resolution time depend on the incident.
15 min
Available P1 response target
Runbooks
Environment-specific procedures
Scheduled
Post-incident review
Blameless
Postmortem culture
Illustrative Incident Flow
P1: Alert → Response → Recovery
Alert Detected
SLO / alertAn SLO breach or actionable database alert opens the incident workflow
On-Call Acknowledges
Plan targetThe assigned engineer accepts the page and starts triage
Impact and Cause Assessed
Runbook-guidedEnvironment-specific runbooks guide diagnosis and escalation
Mitigation Applied
Change-controlledUse an approved rollback, failover, configuration change, or containment step
Recovery Verified · Review Opened
Follow-upConfirm stability, document the timeline, and assign corrective actions
Illustrative sequence only · response target is separate from resolution time
Remote coverage model
Global database support, aligned to your coverage plan.
For qualifying managed-service engagements, JusDB responds to database incidents during agreed coverage hours and against agreed response targets. Staffing, handoffs, escalation paths, and environment access are documented during onboarding.
Illustrative Client Infrastructure
10 example locations · not live telemetry
Remote
Global delivery model
Support for distributed teams and production environments
Scoped
Coverage by agreement
Hours, severity definitions, and response targets are documented
Runbook
Environment onboarding
Topology, access, escalation, and recovery procedures
Hybrid
Deployment coverage
AWS · Azure · Google Cloud · Oracle Cloud · on-premises
Regions are representative examples of where clients run infrastructure JusDB manages remotely. They are not staffed offices, a staffing map, or live service-health data. On-call staffing is defined separately in each service agreement.
Core services
Database reliability services for production systems.
Choose ongoing operations, database SRE, controlled automation, or a focused cost-optimization engagement.
14 database engines, plus Apache SeaTunnel for CDC and data integration.
Production support across SQL, NoSQL, search, analytics, and caching technologies. For MySQL architecture, InnoDB, replication, and upgrades, explore our MySQL consulting services.
Support for the environments in your production stack.
We work across AWS, Azure, Google Cloud, Oracle Cloud, and on-premises infrastructure. Platform and managed-service coverage is confirmed during discovery for your exact services, versions, and architecture.
A Scoped Operating Model
Monitoring, incident response, reviews, and change control — designed around your environment.
For managed engagements, the exact tools, cadence, communication channels, response targets, and reliability commitments are defined in the selected plan and signed scope.
Typical Observability Coverage
Metrics
Typical tools · Prometheus · Grafana
Where included, database exporters, service-level indicators, and burn-rate alerts are configured for the agreed SLOs.
Logs
Typical tools · Loki · ELK · pgBadger
Log collection and alerting can cover slow queries, database errors, replication issues, and authentication events.
Traces
Typical tools · Jaeger · Tempo
When application tracing is in scope, traces help connect expensive queries to the services and requests that generated them.
Example Operations Cadence
Health Review
- Configuration drift
- Backup job status
- Security patch status
- Replication health
Performance Report
- Query and capacity trends
- Cost review
- SLO reporting where contracted
- Prioritized recommendations
Architecture Review
- Scaling readiness
- Technology roadmap
- HA/DR test review
- Upgrade planning
Strategic Planning
- Budget inputs
- Technology evaluation
- Operating-model review
- Compliance readiness support
Plan & Communication
Security & Compliance Support
See how JusDB Autopilot surfaces database risks and recommended changes.
This walkthrough uses sample telemetry to demonstrate detection, diagnosis, and recommendations. Production actions follow your agreed access, approval, and pre-authorized automation controls.
demo@example.com
JusDB Autopilot
Interactive product demonstration using sample fleet data
Autopilot Intelligence
Workload analysis with reviewable, approval-controlled actions
Cluster Status Overview
Sample-MySQL
Sample MySQL cluster v8.0.35
Sample-PostgreSQL
Sample analytics PostgreSQL cluster v15.4
Sample-Redis
Sample Redis cache cluster v7.0.12
Sample-MongoDB
Sample MongoDB document cluster v6.0.8
Sample-Elasticsearch
Sample Elasticsearch cluster v8.9.2
Recent Autopilot Activity
Pre-approved query optimization applied
Sample-MySQL
Pre-approved connection-pool change applied
Sample-PostgreSQL
Index optimization scheduled
Sample-MongoDB
See how Autopilot fits your workflow
Review the product walkthrough, then discuss integrations, permissions, and approval gates for your environment. Recommendations and pre-approved automation support engineering decisions; they do not bypass production change control.
30-minute database assessment
Start with the database problem that matters now.
We'll review the issue, your current architecture, and the outcome you need, then outline the evidence and work required to choose a practical next step.
No production access is required for the first conversation. Availability and incident-response commitments depend on the supported architecture, selected service plan, and signed scope.