Kiyesi

Show us your server's grade 👇 1. Run: sudo kiyesi scan 2. Fix what it finds 3. Scan again Reply with your before and after. A 100/100 gets a shoutout. kiyesi.dev

Picture it: Friday evening, the shop is busy, and customers hit a browser warning because the SSL cert expired two days ago. Avoidable in 3 steps: 1. Know when certs expire 2. Automate renewal 3. Get alerted before expiry What's your "we forgot to renew it" story?

Honest poll: when did you last check your server's firewall? No judgment. Reply with the story if you've got one

From C to A in about a minute. Kiyesi scans your Linux server, explains each problem in one sentence, and gives you the commands to fix it. You review and run them. It never changes anything itself. Free for one server: kiyesi.dev?

SSH password login still on? Bots try to guess it all day. Before you turn it off, open a second terminal and confirm your key works. Otherwise you can lock yourself out. The fix is in the image. Not sure what else is exposed? Run: sudo kiyesi scan #Linux #SSH

"How I Recovered 35GB on a Production Server by Moving Docker Builds Off It" by @SamuelFolasayo #DEVCommunity dev.to/saint_vandora/how-i-r…

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 ])

Why Use Aggregation? Perform data analysis inside MongoDB. Reduce round-trips by moving logic to the database. Powerful for reporting, analytics, dashboards.

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

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.

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.

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.

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).

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.

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.

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.

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.