Global MongoDB Architects
MongoDBMongoDB
Services
Engineered.
MongoDB is a distributed document database engineered for flexible JSON/BSON schemas, high-throughput transactional scale, and horizontal sharding. JusDB delivers specialized MongoDB database reliability engineering—covering replica set automated failover, WiredTiger cache tuning, aggregation pipeline optimization, and low-downtime Atlas migrations. Availability and response commitments are defined in your service agreement; 24x7 on-call is available under your service agreement.
Your MongoDB cluster is the beating heart of your product. When a COLLSCAN hits your largest collection at peak traffic, you need engineers who have already diagnosed — and fixed — that exact problem.
From a 4-second aggregation pipeline to a low-downtime Atlas migration — we've seen it, fixed it, and documented the runbook. MongoDB-native engineers, not generalists.
7.0 and 8.0
MongoDB versions
30 minutes
P1 target with 24x7 on-call
2 to 4 hours
Business-hours initial-response target
MongoDB 7.0 · 3-node replica set
PRIMARY + 2 SECONDARY · WiredTiger
2.43k
97.8%
3ms
184
Query Throughput
2.43k ops/s[OK] replset: PRIMARY rs0/node-01:27017, election clean
[INF] oplog: window 72h, SECONDARYs lag 0ms
[OK] wiredTiger: cache 97.8% hit, 0 evictions
[INF] balancer: chunk shard-02 → shard-03 complete
Example monitoring view showing database activity and engineer actions. Uses sample data, not customer data.
MongoDB 5.0 reached End of Life in October 2024 — and 6.0 has now followed. Still on 5.0 or 6.0? You're already running unsupported — upgrade to 7.0+ now, where MongoDB 8.0 delivers significant query engine improvements.
24
Supported database technologies
24x7
On-call coverage, under your service agreement
30 min
P1 initial-response target on 24x7 on-call
2 to 4 h
Initial-response target in covered business hours
Full-Spectrum MongoDB
Engineering
From a 4-second aggregation to a low-downtime Atlas migration — we've seen it, fixed it, and documented the runbook.
Performance Tuning
explain() plan analysis, index strategy (compound, partial, TTL), aggregation pipeline optimisation, and WiredTiger cache tuning.
High Availability & DR
Replica set design, arbiter configuration, priority tuning, and cross-region secondary placement for fast automatic elections.
Sharding & Scaling
Shard key design to eliminate hotspots, zone sharding for data locality, balancer tuning, and chunk migration analysis.
Atlas & Cloud Migration
Self-hosted → Atlas migrations using mongomirror / Live Migration Service, plus cross-cloud moves with low-downtime Change Stream sync.
Managed DBA Service
Continuous automated monitoring, index bloat management, oplog sizing, backup verification (Ops Manager / Atlas backups), and capacity planning.
Security & Compliance
Field-level encryption (FLE), RBAC design, TLS enforcement, auditing, network peering, and hardening for SOC 2, HIPAA, and PCI DSS.
From Slow to Blazing Fast
in Days, Not Months
We don't guess — we instrument. Our systematic approach combines explain() plan analysis, Atlas Performance Advisor, and schema pattern review, with query latency measured against your baseline before and after every change.
Query Performance
After tuningIllustrative health scores · results depend on the workload
Queries We've Transformed
Click any card to reveal the fix.
4,200ms
2ms
COLLSCAN — 8.1M docs
The fix
db.orders.createIndex({ user_id: 1, status: 1, created_at: -1 })
7,800ms
44ms
2,100 separate find() calls
The fix
Rewrote client-side loop as a single $lookup aggregation pipeline
9,600ms
11ms
Array grow: 120k elements per doc
The fix
Applied bucket pattern — split array into fixed-size sub-documents
Pre-Migration Assessment
MongoDB 4.4 → 7.0 upgrade
Estimated cutover window: < 10 minutes
Move to Atlas
With Minimal Downtime
Atlas migrations fail when the oplog window closes mid-sync. We pre-size your oplog, run mongomirror with lag monitoring, and execute cutover only when replica lag hits zero, with a short, rehearsed application pause and a pre-validated rollback at every step.
P1 to Resolved
Average: 14 Minutes
When a COLLSCAN or replica election brings production down, every second counts. Our on-call DBAs follow a battle-tested runbook — from the first alert to root-cause fix, you see every step in real time.
Oplog lag above 60s on SECONDARY node-02
A named MongoDB DBA responds within your agreement's initial-response target
Missing compound index: COLLSCAN on orders (8M docs)
createIndex({ user_id: 1, status: 1 }) built without blocking reads and writes
Oplog lag back to baseline; index added to the schema review; post-incident review
Always On.
Engineered That Way.
We design and operate MongoDB replica sets that survive primary elections — tested and rehearsed, with tuned election timeouts and cross-region secondaries. Availability targets are agreed per workload and written into your service agreement.
3/3
Members online
<10s
Election RTO
0ms
Replica Lag
Remote DBAs for
Clusters Anywhere
Our engineering team is in India; business-hours coverage is Mon–Fri 09:00–18:00 IST (UTC+5:30), and 24x7 on-call is available under your service agreement. No outsourced answering service — MongoDB engineers who know your cluster.
IST
Engineering team time zone
24x7
On-call, under your service agreement
30 minutes
P1 initial-response target (24x7 on-call)
Named
Engineer owns each incident
Not Just DBAs. MongoDB SREs.
We tie every engagement to measurable SLOs, with replica set drills, automated index health monitoring, and post-incident reports with prevention plans scoped into your service agreement.
MongoDB-Native Engineers
Engineers who work on MongoDB internals: high-traffic OLTP, Atlas deployments, and sharded clusters.
Systematic Tuning Framework
explain() analysis, Atlas Performance Advisor, and schema pattern review — not guesswork. Query latency is measured against your baseline before and after every change.
Tested Failover
We design replica sets for fast, automatic primary elections, and test them with failover drills and oplog-verified restores. Drill cadence and availability commitments are set in your service agreement.
Agreed Response Targets
Initial-response targets are 2 to 4 hours during covered business hours, Mon–Fri 09:00–18:00 IST (UTC+5:30). Where your service agreement includes 24x7 on-call, the initial-response target for P1 incidents is 30 minutes. Targets are not resolution guarantees. Escalation paths and runbooks are written into your service agreement.
Atlas & Cloud-Native
MongoDB Atlas, Amazon DocumentDB, Kubernetes operators, and self-hosted — we architect for the deployment model your workload and budget actually need.
Compliance-First Mindset
Every engagement includes a security baseline: RBAC audit, TLS verification, Field Level Encryption review, and SOC 2 / HIPAA / PCI DSS alignment.
The Full MongoDB Ecosystem
We cover every flavour of MongoDB — from self-hosted replica sets to fully managed Atlas and cloud-native deployments.
Specialized MongoDB Services
Each service is its own craft. Pick the one you need — or let us assemble a program.
MongoDB Consulting
Architecture design, schema modelling, sharding strategy, and health checks.
Performance Tuning
explain() plans, index strategy, aggregation pipeline, WiredTiger tuning.
Migration Services
RDBMS → MongoDB, version upgrades, and Atlas live migrations.
MongoDB DBA Support
Agreed incident response, monitoring, and proactive maintenance.
High Availability
Replica sets, sharding, election tuning, and DR architecture.
Remote DBA
Hire a dedicated, retained engineer for your fleet — typically far cheaper than in-house staffing.
MongoDB Atlas
Cluster sizing, Atlas Search, Data Federation, triggers, and fully managed cloud operations.
MongoDB on Kubernetes
MongoDB & Percona operators, StatefulSets, storage classes, and self-healing deployments.
Security Audit
CSFLE, x.509, Atlas KMS, RBAC review, and SOC 2 / HIPAA / PCI DSS hardening.
How We Work Together
Three engagement models — pick the one that fits where you are right now.
MongoDB Assessment
Fixed scope, quoted after a scoping call
A deep-dive audit of your MongoDB environment. We deliver a written report covering slow queries, index gaps, schema anti-patterns, HA configuration, and a prioritised remediation roadmap — within 5 business days.
Migration or Tuning Project
Scoped on call
A defined-scope engagement — an Atlas migration, version upgrade, sharding implementation, or systematic performance tuning program. Fixed price once scoped.
Managed DBA Service
Monthly retainer
Ongoing operations under a monthly retainer; contract terms are set in your service agreement. Two ways in: a named, retained engineer for your fleet (Remote DBA) or agreed incident response (Support) — pick the model that fits.
Need a named engineer on retainer? See Remote DBA. Need agreed incident response, with 24x7 on-call available? See MongoDB Support. All engagements start with a free 30-minute scoping call. Book yours →
MongoDB Internals: Critical Failure Modes
Default cloud MongoDB deployments and Atlas defaults rarely protect against extreme transaction concurrency or runaway aggregations. Here are the failure modes our DBRE team diagnoses and mitigates:
Unindexed $lookup Aggregation & 100MB RAM Disk Spill
An aggregation pipeline with an unindexed $lookup stage performs an exhaustive nested-loop collection scan on millions of documents. Exceeding the 100MB RAM working memory ceiling forces WiredTiger to spill temporary files to disk, saturating disk IOPS and causing cascading query timeouts.
We design foreign-field indexes on joined collections, rewrite pipelines to push $match and $project stages before joins, and configure selective indexing so lookups are fully covered in memory.
Oplog Window Depletion & Standby Replica Desynchronization
A massive batch write or schema migration exhausts the capped oplog collection window faster than secondaries can replay transactions. Lagging secondaries drop into a permanently broken RECOVERING state and require a full multi-day initial sync from scratch.
We monitor real-time oplog GB/hour generation rates, tune oplogSizeMB dynamically based on workload write velocity, and configure secondary delay alarms to prevent replication gaps.
Monotonically Increasing Shard Key & Jumbo Chunk Freezes
Selecting an auto-incrementing ObjectId or timestamp as a shard key routes 100% of write throughput to the highest chunk on a single shard node. The chunk grows beyond maximum chunk size and becomes an un-splittable jumbo chunk, freezing balancer operations.
We architect compound hashed shard keys (e.g. { tenant_id: 'hashed', created_at: 1 }) to distribute writes evenly across shards while preserving efficient range-query routing.
Our MongoDB SREs execute read-only diagnostic telemetry to isolate long-running operations and evaluate WiredTiger dirty cache pressure without interrupting production throughput:
db.currentOp({
"active": true,
"secs_running": { "$gt": 5 },
"op": { "$in": ["query", "update", "delete", "getmore"] },
"ns": { "$ne": "local.oplog.rs" }
}, {
"opid": 1,
"secs_running": 1,
"ns": 1,
"command": 1,
"numYields": 1,
"waitingForLock": 1,
"lockStats": 1,
"client": 1
});db.runCommand({
serverStatus: 1,
wiredTiger: 1,
oplatencies: 1
}).wiredTiger.cache;
// Key production health indicators:
// 1. "tracked dirty bytes in the cache" < 20% max
// 2. "bytes currently in the cache" < 80% max
// 3. "pages evicted by application threads" == 0
// (nonzero indicates background eviction starvation)How JusDB MongoDB Services compare to alternative options.
Running MongoDB at scale requires deep understanding of WiredTiger cache mechanics, aggregation memory limits, and shard key cardinality. Here is how JusDB compares to Atlas support, generic MSPs, and internal dev teams.
| Engineering Dimension | JusDB MongoDB SRE | MongoDB Atlas Support | Generic MSPs | In-House Devs |
|---|---|---|---|---|
| COLLSCAN Elimination & Index Architecture | Exhaustive explain('executionStats') profiling, ESR rule compound indexing, partial/TTL/wildcard filters, and aggregation pipeline optimization | Automated Performance Advisor suggests basic single-field indexes without analyzing write amplification or aggregation stages | Basic index recommendations based on slow query thresholds without understanding WiredTiger cache evictions | Unindexed collections running COLLSCANs on multi-million document collections, exhausting CPU and RAM |
| Sharding & Chunk Balance Architecture | Hashed and compound ranged shard key design, zone sharding for data locality, and jumbo chunk split remediation preventing hotspots | Enables sharding via web console; customer is left to choose shard keys, risking irreversible hotspotting and expensive re-sharding | Lacks deep distributed sharding expertise; struggles to balance chunk migrations across mongos routers | Selected monotonically increasing shard key (_id, timestamp) resulting in 100% of write traffic hitting a single shard |
| Replica Set Elections & Automatic Failover | Tuned election priorities and heartbeat settings, hidden secondaries for DR, and failover timing tested against your RTO target | Standard automated failover takes 10–30 seconds with client driver reconnect storms and transient query timeouts | Standard 3-node replica sets without disaster recovery secondary routing or cross-region quorum verification | Default replica set configurations causing election deadlocks and split votes during transient network blips |
| Incident Response & Escalation | Named MongoDB engineers join your incident bridge. Initial-response targets: 2 to 4 hours in covered business hours; 30 minutes for P1 incidents with 24x7 on-call. Targets, not resolution guarantees. | Multi-tiered support queue; requires paid enterprise support plan with 1-hour P1 response and ticket portal communication | Offshore ticket triage by generic sysadmins who lack MongoDB engine internals and WiredTiger knowledge | Exhausted on-call developers waking up to opaque MongoDB driver timeout errors without root-cause tooling |
| Low-Downtime Migration & Live Cutover | Low-downtime migrations from on-prem or cloud to MongoDB Atlas using Change Streams and mongomirror, with short, rehearsed cutovers and rollback safety | Live Migration Service handles basic moves but fails on high-write volumes or complex network VPC peering configurations | Requires multi-hour maintenance windows with offline mongodump and mongorestore causing extended downtime | Risky manual dump/restore scripts that fail mid-transfer or drop oplog timestamps, risking data loss |
| Security, CSFLE & Compliance Hardening | Client-Side Field Level Encryption (CSFLE), Queryable Encryption, x.509 cert authentication, and granular RBAC aligned with SOC 2 & HIPAA | Basic Atlas security settings enabled, but customer must implement and manage field encryption keys and application roles | Basic username/password authentication without encrypted communication or audit log pipeline integration | Admin credentials shared in application connection strings with unrotated static passwords and open network access |
Common Questions
Real answers from real MongoDB engineers — no sales fluff.
Do you provide 24/7 MongoDB DBA support?
Yes, 24x7 on-call is available under your service agreement; otherwise coverage is business hours. Initial-response targets are 2 to 4 hours during covered business hours, Mon–Fri 09:00–18:00 IST (UTC+5:30). Where your service agreement includes 24x7 on-call, the initial-response target for P1 incidents is 30 minutes. Targets are not resolution guarantees.
What versions of MongoDB do you support?
MongoDB 7.0 and 8.0, plus MongoDB Atlas, Amazon DocumentDB, and Azure Cosmos DB for MongoDB, on self-hosted replica sets and managed deployments. MongoDB 6.0 and older are past end of life, so for those we plan the upgrade path to a supported release first.
Can you migrate from a relational database to MongoDB?
Yes. We handle MySQL, PostgreSQL, and Oracle to MongoDB migrations: document schema design, data transformation pipelines (Debezium or custom ETL), and a cutover backed by change data capture so the target stays in sync until the switch.
How quickly can you start?
We start once the engagement is agreed and access is in place, on a date confirmed in your proposal.
Do you design sharded clusters?
Yes. We design shard key strategies to avoid hotspots, implement zone sharding for data locality, and size the cluster for your throughput and storage growth. We also audit existing sharding configurations for performance issues.
What does your query optimisation process look like?
We use MongoDB's explain() plan analysis, the Atlas Performance Advisor, and custom $currentOp queries to identify slow queries, then fix them through index creation (including partial, TTL, and compound indexes), aggregation pipeline rewrites, and schema pattern improvements (bucket, outlier, computed).
Can you manage our MongoDB Atlas deployment?
Yes. We manage Atlas project configuration, cluster sizing, Atlas Search indexes, Data Federation, and triggers. We also set up Atlas Alerting and connect to your existing observability stack (Datadog, Grafana, PagerDuty).
Ready to Scale Your
MongoDB System?
Bring us your production MongoDB clusters, from 100GB OLTP replica sets to multi-TB sharded deployments on Atlas.
No commitment
First assessment is free
Fast start
DBA on your env in 24h
Zero lock-in
Month-to-month contracts
Explore Our MongoDB Services
Comprehensive MongoDB solutions tailored to your enterprise database needs
MongoDB Consulting
Senior DBAs for schema design, shard-key selection, Atlas optimization & health checks
Learn moreMongoDB Support
Enterprise MongoDB incident response and replica failover triage; 24x7 on-call available
Learn moreMongoDB Migration & Upgrades
Low-downtime MongoDB version upgrades, cross-platform migrations & Atlas cutovers
Learn moreMongoDB High Availability
Replica sets, automatic election failover & multi-region DR
Learn moreMongoDB Performance Tuning
Aggregation pipeline optimization, COLLSCAN elimination & WiredTiger cache tuning
Learn moreMongoDB Remote DBA
Dedicated remote DBAs, proactive monitoring & Atlas scaling, without a full-time hire
Learn moreMongoDB on Kubernetes
Production K8s deployments via MongoDB Community / Enterprise operators and Percona PSMDB
Learn moreMongoDB Atlas
Atlas cluster design, tier sizing, Atlas Search, and managed operations across AWS, GCP & Azure
Learn moreMongoDB Security Audit
Authentication, RBAC, encryption-at-rest/in-transit, and compliance control mapping
Learn more