Kiyesi

Kiyesi helps teams monitor server health, detect security issues, and fix infrastructure problems with simple, actionable automation.

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"How I Recovered 35GB on a Production Server by Moving Docker Builds Off It" by @SamuelFolasayo #DEVCommunity https://t.co/dumRLWScb8

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Aggregation pipelines use stages to transform documents step by step:

db.orders.aggregate([
{ $match: { status: "completed" } }, // filter
{ $group: { _id: "$customerId", totalSpent: { $sum: "$amount" } } }, // group + sum
{ $sort: { totalSpent: -1 } } // sort
])

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Why Use Aggregation?

Perform data analysis inside MongoDB.

Reduce round-trips by moving logic to the database.

Powerful for reporting, analytics, dashboards.

[Kiyesi @kiyesi_tech]

Aggregation in MongoDB processes data records and returns computed results.
Think of it as MongoDB’s version of SQL’s GROUP BY + HAVING + JOIN.

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You’ll learn, connect, and even earn a @MongoDB Skill Badge in a hands-on workshop.

Don’t miss this big one! 💚

👉 Register here: https://t.co/agt0Rgq7Y9

#MongoDB #NoSQL

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We’re bringing the MongoDB Lagos community together again! On November 1st at Makanjuola Hall, Lagos State University, Ojo Campus! We’ll be talking about how AI and vector search are shaping the future of intelligent apps.

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Performance Tuning In MongoDB
Monitoring & Tools

Use MongoDB Atlas Performance Advisor.

Monitor with mongostat and mongotop.

Set up alerts for slow queries and resource bottlenecks.

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Performance Tuning In MongoDB
Write & Read Tuning

Use write concern wisely — don’t overcommit if not needed.

Use read preference (nearest/secondary) to distribute load.

Enable connection pooling for high-concurrency apps.

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Performance Tuning In MongoDB
Schema Design
Embed when data is accessed together (fewer joins).

Reference for large or frequently updated data.

Avoid documents nearing the 16MB limit.

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Performance Tuning In MongoDB
Hardware & Resources

Ensure sufficient RAM to keep working set in memory.

Use SSD storage for faster disk operations.

Monitor IOPS (input/output operations per second).

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Performance Tuning in MongoDB
Query Optimization

Use .explain("executionStats") to analyze queries.

Avoid $where and overly complex $regex queries.

Prefer projections to fetch only required fields.

[Kiyesi @kiyesi_tech]

Performance Tuning in MongoDB
Query Optimization

Use .explain("executionStats") to analyze queries.

Avoid $where and overly complex $regex queries.

Prefer projections to fetch only required fields.

[Kiyesi @kiyesi_tech]

1. Index Optimization

Create indexes based on query patterns.

Avoid over-indexing (too many indexes slow writes).

Use covered queries to reduce disk I/O.

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2️⃣ Storage Implications

Decimal128 ensures precision but takes more storage than double or int.

Large BSON documents = more RAM & disk usage.

Choosing the right type keeps working set size smaller → better cache utilization.

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How BSON Type Choices Affect Query Performance
Smaller types = faster queries (e.g., int32 is faster than int64 if values fit)
Choosing the wrong type can force MongoDB to do type conversions → slowing down queries.
Index efficiency improves when using consistent, compact types

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3️⃣ Handling UUIDs Effectively

MongoDB supports UUID subtype within BinData.

UUIDs provide globally unique identifiers (better than ObjectIds when cross-system consistency is needed).

Useful for distributed systems, microservices, and external integrations.

[Kiyesi @kiyesi_tech]

2️⃣ Use Cases for BinData

File storage → Small images, thumbnails, audio snippets.

Encryption → Store encrypted fields or hashes securely.

Custom application data → Game assets, device firmware, IoT payloads

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1️⃣ Storing Binary Data in MongoDB

MongoDB supports BinData type for raw binary data.

Commonly used for images, files, or encrypted content.

⚠ Best practice: Avoid putting very large files directly in documents. Instead, use GridFS for files >16MB.