惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

H
Heimdal Security Blog
小众软件
小众软件
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
罗磊的独立博客
Google DeepMind News
Google DeepMind News
大猫的无限游戏
大猫的无限游戏
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Hugging Face - Blog
Hugging Face - Blog
阮一峰的网络日志
阮一峰的网络日志
A
About on SuperTechFans
宝玉的分享
宝玉的分享
博客园 - 聂微东
月光博客
月光博客
Cyberwarzone
Cyberwarzone
Microsoft Security Blog
Microsoft Security Blog
V
Visual Studio Blog
Project Zero
Project Zero
T
Tor Project blog
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
L
LINUX DO - 最新话题
博客园 - 叶小钗
Recent Commits to openclaw:main
Recent Commits to openclaw:main
Attack and Defense Labs
Attack and Defense Labs
Spread Privacy
Spread Privacy
Forbes - Security
Forbes - Security
Simon Willison's Weblog
Simon Willison's Weblog
N
Netflix TechBlog - Medium
P
Proofpoint News Feed
Engineering at Meta
Engineering at Meta
Hacker News: Ask HN
Hacker News: Ask HN
I
InfoQ
M
MIT News - Artificial intelligence
AI
AI
博客园 - 三生石上(FineUI控件)
W
WeLiveSecurity
C
Check Point Blog
The Hacker News
The Hacker News
C
Cyber Attacks, Cyber Crime and Cyber Security
Application and Cybersecurity Blog
Application and Cybersecurity Blog
T
Tenable Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
The Cloudflare Blog
Blog — PlanetScale
Blog — PlanetScale
美团技术团队
D
Darknet – Hacking Tools, Hacker News & Cyber Security
GbyAI
GbyAI
Hacker News - Newest:
Hacker News - Newest: "LLM"
腾讯CDC
K
Kaspersky official blog

Blog — PlanetScale

Keeping a Postgres queue healthy — PlanetScale Patterns for Postgres Traffic Control — PlanetScale Graceful degradation in Postgres — PlanetScale High memory usage in Postgres is good, actually — PlanetScale Stripe Projects partnership: Provision PlanetScale Postgres and MySQL databases from the Stripe CLI — PlanetScale Enhanced tagging in Postgres Query Insights — PlanetScale Behind the scenes: How Database Traffic Control works — PlanetScale Introducing Database Traffic Control — PlanetScale Scaling Postgres connections with PgBouncer — PlanetScale Drizzle joins PlanetScale — PlanetScale Video Conferencing with Postgres — PlanetScale Faster PlanetScale Postgres connections with Cloudflare Hyperdrive — PlanetScale Introducing the PlanetScale MCP server — PlanetScale Database Transactions — PlanetScale Automating our changelog with Cursor commands — PlanetScale Postgres 18 is now available — PlanetScale Using MotherDuck with PlanetScale — PlanetScale $50 PlanetScale Metal is GA for Postgres — PlanetScale AI-Powered Postgres index suggestions — PlanetScale $5 PlanetScale is live — PlanetScale Announcing Vitess 23 — PlanetScale $50 PlanetScale Metal — PlanetScale Report on our investigation of the 2025-10-20 incident in AWS us-east-1 — PlanetScale $5 PlanetScale — PlanetScale Benchmarking Postgres 17 vs 18 — PlanetScale Larger than RAM Vector Indexes for Relational Databases — PlanetScale Partnering with Cloudflare to bring you the fastest globally distributed applications — PlanetScale Processes and Threads — PlanetScale PlanetScale for Postgres is now GA — PlanetScale Postgres High Availability with CDC — PlanetScale Announcing Neki — PlanetScale Caching — PlanetScale The principles of extreme fault tolerance — PlanetScale Announcing PlanetScale for Postgres — PlanetScale Benchmarking Postgres — PlanetScale Announcing Vitess 22 — PlanetScale The Real Failure Rate of EBS — PlanetScale IO devices and latency — PlanetScale Announcing PlanetScale Metal — PlanetScale PlanetScale Metal: There’s no replacement for displacement — PlanetScale Upgrading Query Insights to Metal — PlanetScale Automating cherry-picks between OSS and private forks — PlanetScale Database Sharding — PlanetScale Anatomy of a Throttler, part 3 — PlanetScale Introducing sharding on PlanetScale with workflows — PlanetScale Announcing Vitess 21 — PlanetScale Announcing the PlanetScale vectors public beta — PlanetScale Anatomy of a Throttler, part 2 — PlanetScale Instant deploy requests — PlanetScale Anatomy of a Throttler, part 1 — PlanetScale Increase IOPS and throughput with sharding — PlanetScale Tracking index usage with Insights — PlanetScale Faster backups with sharding — PlanetScale Building data pipelines with Vitess — PlanetScale The State of Online Schema Migrations in MySQL — PlanetScale Optimizing aggregation in the Vitess query planner — PlanetScale Dealing with large tables — PlanetScale Announcing Vitess 20 — PlanetScale Self-managed Vitess vs Managed Vitess with PlanetScale — PlanetScale Achieving data consistency with the consistent lookup Vindex — PlanetScale The MySQL adaptive hash index — PlanetScale Introducing global replica credentials — PlanetScale Profiling memory usage in MySQL — PlanetScale Summer 2023: Fuzzing Vitess at PlanetScale — PlanetScale How PlanetScale makes schema changes — PlanetScale Identifying and profiling problematic MySQL queries — PlanetScale The Problem with Using a UUID Primary Key in MySQL — PlanetScale Announcing Vitess 19 — PlanetScale PlanetScale forever — PlanetScale Introducing schema recommendations — PlanetScale Amazon Aurora Pricing: The many surprising costs of running an Aurora database — PlanetScale Three common MySQL database design mistakes — PlanetScale OAuth applications are now available to everyone — PlanetScale Deprecating the Scaler plan — PlanetScale PlanetScale branching vs. Amazon Aurora blue/green deployments — PlanetScale Databases at scale — PlanetScale Considerations for building a database disaster recovery plan — PlanetScale Working with Geospatial Features in MySQL — PlanetScale PlanetScale vs Amazon Aurora replication — PlanetScale Introducing the Vantage and PlanetScale integration — PlanetScale MySQL isolation levels and how they work — PlanetScale Introducing the schemadiff command line tool — PlanetScale $ pscale ping — PlanetScale Announcing foreign key constraints support — PlanetScale The challenges of supporting foreign key constraints — PlanetScale What is HTAP? — PlanetScale Introducing Insights Anomalies — PlanetScale Webhook security: a hands-on guide — PlanetScale MySQL replication: Best practices and considerations — PlanetScale A guide to HTML email with Ruby on Rails and Tailwind CSS — PlanetScale Sharding for cost-effective database management — PlanetScale PlanetScale ranks 188th in Deloitte’s top 500 fastest-growing companies — PlanetScale Announcing the Fivetran integration — PlanetScale Introducing webhooks — PlanetScale What is MySQL replication and when should you use it? — PlanetScale Sync user data between Clerk and a PlanetScale MySQL database — PlanetScale Introducing database reports — PlanetScale Distributed caching systems and MySQL — PlanetScale What is MySQL partitioning? — PlanetScale MySQL High Availability: Connection handling and concurrency — PlanetScale
How PlanetScale prevents MySQL downtime — PlanetScale
Sam Lambert · 2022-08-02 · via Blog — PlanetScale

Sam Lambert [@samlambert] |

The cost of downtime can range from loss of business to severe reputation damage. Database downtime feels inevitable but is often preventable.

The causes of database issues that lead to downtime can be categorized in the following ways:

  • Human error
  • System immaturity
  • Application issues

In this post, we will explore how PlanetScale can mitigate all three.

Downtime due to human error

We’ve all done it, dropped the wrong table or index and caused queries to dramatically slow or fail. This can lead to entire site outages, as well as cascading failure that impacts other systems. With standard MySQL, if you drop a table that you later find out was still in use, you are in a situation where you now have to restore from backup. Selecting the right backup, restoring, and bringing your site back online can take hours, which of course leads to high levels of stress for you and your team.

To help prevent this type of outage, PlanetScale warns you if the table to be dropped was recently queried. This will help you avoid the mistake of dropping a table that is in use.

Deploy request warning

If you do happen to deploy a schema that has issues, such as a sub-optimal index that causes query performance degradation or a dropped column that cause errors, we also let you roll back the schema deployment without any loss of data.

Downtime due to system immaturity

Building a highly available database is hard. It takes decades for databases to come to maturity. People often bet on solutions that have traded scalability for approachability. On the surface, this feels like the right trade off when you are just starting a project, but can very quickly backfire when user demand for your services increases.

We have built PlanetScale on top of Vitess, the database clustering system for horizontal scaling of MySQL, which was built by the database team at YouTube to power YouTube.com. Since Vitess was open sourced, it has been adopted by GitHub, Slack, Etsy, Roblox, and many more. PlanetScale are also the maintainers of Vitess.

Being used and contributed to by some of the largest sites on the internet means that Vitess has been pressure tested at scale.

The reason we chose to build PlanetScale on top of Vitess starts with our fundamental belief in the importance of developer experience. Developer experience starts with approachability but is only maintained with reliability and scalability. Building on a database platform that supports billions of users ensures that our users will not be forced to trust an immature system. We know Vitess scales and will work for the people that trust us with one of the most critical pieces of their application.

Downtime due to application issues

Bugs happen. You can’t deploy perfect software all the time. A common reason for database outages is bad application deploys causing spikes of excessive database load. This can be caused by poorly performing (slow) queries or too many queries at once.

PlanetScale Insights is a next generation monitoring solution that helps you discover bad queries in real time. When we receive a query from your application, we send it through a data pipeline that logs the query and its performance metrics. This allows you to gain an aggregated view of the queries your application sends. Finally, you can use query comments to tag and identify the source of queries.

PlanetScale Insights database activity graph

PlanetScale Insights queries over 24 hours

Try it out

At PlanetScale, we’re committed to delivering a high-performance scalable database that doesn’t require you to give up developer experience. Vitess allows us to build on a proven mature solution. And we will continue to ship new in-dashboard tools and alerts to help you identify issues caused by application code or human error before they make it to production.

You can sign up for an account or contact us today to get started.