devopsy.kinsta.cloud

Author: Nick Van Wiggerern

  • Best Practices for Configuring MySQL Replication

    Best Practices for Configuring MySQL Replication

    MySQL provides several replication configuration options. However, ensuring it is done correctly may take time and effort, with considerable choices. Replication is a crucial initial step to enhance availability in MySQL databases. A properly designed replication architecture can significantly impact the accessibility of your data and prevent potential management complications. This article will delve into best practices for replication, covering local and long-distance scenarios.

    Active and Passive Setups

    When using active/passive mode for replication in MySQL, one server acts as the source while others serve as read-only replicas. The replicas can handle read-only queries, but all writes must be directed to the source. This configuration distributes the load across all replicas. Still, in the default asynchronous replication mode, there might be a delay between when data is written to the source and when it’s available on the replica. Keep this in mind while designing your application.

    Alternatively, the active/active configuration allows multiple servers to handle both read and write operations. While it may seem beneficial to have two servers for write requests, each server still needs to process the query workload of the other, making write distribution less effective. Additionally, MySQL lacks native conflict resolution logic, so conflicts can quickly arise, making it challenging to determine the true source of data without significant data loss when a rebuild is necessary.

    I recommend using the active/passive configuration for replication and sharding if you require higher throughput from your database.

    Enable GTIDs

    Global transaction identifiers (GTIDs) are unique IDs attached to transactions in a replicated environment. By default, replicas track processed records in the binary log file of a source database. However, this method is fragile if the source crashes and logs need to be restored.

    With GTIDs enabled, each transaction receives a UUID-based ID, allowing replicas to determine if a transaction has been processed. The GTID is a UUID representing the source server, followed by an auto-incrementing ID (e.g., 14a54b2f-2ad0-43b6-b803-72b5d7151d3b:1). As transactions occur on the source, the UUID remains the same while the ID increases. When a replica processes a transaction, the GTID or GTID range (e.g., 14a54b2f-2ad0-43b6-b803-72b5d7151d3b:1-10) is stored in the gtid_executed table.

    This process significantly reduces the risk of data becoming unsynchronized due to unprocessed or excessively processed transactions.

    Replication Modes for Optimal Configuration

    MySQL offers two replication modes that behave differently and should be understood to ensure optimal configuration for your environment. By default, MySQL employs asynchronous replication, where transactions are sent to the source, read by replicas and processed independently without source validation.

    Alternatively, MySQL supports semi-synchronous replication, enabled as a plugin. In this mode, transactions are received by the source and processed by replicas, but the source waits for at least one replica to accept the transaction before responding. Semi-synchronous replication provides greater data consistency, though it introduces some overhead in response time.

    With semi-sync mode, there are additional options that can be adjusted. By default, the primary server waits 10 seconds for a replica with semi-sync mode enabled to acknowledge the transaction. If data consistency relies on semi-sync, consider increasing this timeout value to ensure guaranteed consistency.

    It’s important to note that these modes can be mixed and matched. For instance, you can configure one replica with semi-sync and another without, ensuring that one specific server always has an up-to-date copy of your database while other replicas catch up at their own pace. This approach aids disaster recovery by easily identifying the best candidate for recovery.

    Understanding the distinctions between these modes will help you make informed decisions that align with your business needs.

    Optimize Replica Instances With Separate Log Storage

    Replica instances in your environment rely on the binary logs of the source for accurate information, as mentioned earlier. These logs are stored on the same disk as the database by default. However, this setup can overwhelm busy databases due to high throughput, including database manipulation and reading binary logs for replication. To address this, storing the binary logs on a separate disk from the database is recommended.

    This approach offers performance benefits and cost savings in cloud environments where free volumes have strict IOPS limits.

    Monitor Replication and Metrics in Managed Clusters

    Monitoring is crucial for all infrastructure, including replication. With monitoring, it is possible to know if data is being replicated after configuration. SolarWinds database performance (formerly VividCortex) and Prometheus are popular solutions for monitoring replication and other metrics in managed clusters. Regardless of the chosen solution, it is essential to promptly notify the appropriate individuals when issues arise and address them before they escalate.

    Create a Failover Plan for Minimizing Disruptions

    Inevitable software or hardware failures necessitate failover planning to minimize potential disruptions. Utilizing replication offers resilience by ensuring multiple servers house your online data simultaneously. Therefore, your team must possess a well-prepared strategy should the primary data source fail. The following example outlines an unplanned failover process:

    ● Ensure the downed source remains offline to avoid unexpected replication issues.
    ● Identify and remove the read_only option from the chosen replica that will serve as the new data source. If using semi-sync, select the replica previously configured with the plugin and source.
    ● Update your application to direct queries to the newly promoted source.
    ● Modify the remaining replicas to start replicating from the new source.

    Optimize Cross-Region Replication

    Cloud providers typically provide services across multiple geographic regions comprising several data centers. These data centers, known as availability zones (AZs), are strategically located within the same region but far enough to withstand disasters. Replicating databases to different physical locations is recommended but requires careful consideration. Replication introduces additional latency due to the distance the data needs to travel. Fortunately, latency between AZs is generally low, with AWS claiming single-digit millisecond latency within the same region.

    In contrast, there is significant latency between regions. For example, at the time of writing, the latency between us-east-1 and us-west-1 was reported to be over 60ms by Cloudping.co. Replication across regions results in replication lag, which is the time difference between data being written to the source and being written to a replica. This lag is even more pronounced when replicating across longer distances.

    Asynchronous mode should be used for replication across regions to avoid unnecessary delays for applications making requests.

    A comprehensive understanding of replication configuration options is crucial. However, it is equally important to determine the optimal configuration for these options. This can significantly impact your MySQL cluster’s operational efficiency and data-serving capabilities.

  • Building Scalable Cloud Applications With MySQL

    Building Scalable Cloud Applications With MySQL

    Relational database systems such as MySQL have long been the go-to choice for handling large and complex data handling tasks. But, with the introduction of new technologies like NoSQL, many developers started to question whether traditional relational databases still have the upper hand. However, when building high-scalability cloud applications, relational databases like MySQL still have the edge over NoSQL. Here are five reasons MySQL remains superior to NoSQL in supporting developers of high-scale cloud applications.

    1. Enablement of Complex Queries

    Structured query language (SQL) is the most widely adopted language for relational databases, and MySQL is no different. SQL gives developers a powerful platform for creating complex queries and ad hoc reports, efficiently managing large datasets and creating tables and indexes for data optimization. By contrast, NoSQL usually offers only rudimentary query and data manipulation capabilities, often proving inefficient when handling complex data sets. Most data analysts are also familiar with SQL, so it’s a drop-in tool they can use to help gain insights.

    2. Scalability and Reliability

    MySQL is noted for its scalability when handling massive data loads and is particularly well suited to cloud-based applications that require consistently high performance. MySQL ensures that the consistency of data is maintained. MySQL is the go-to option for scalability and reliability for larger cloud applications. Companies such as Facebook, GitHub and WordPress have built billion-dollar businesses on MySQL, and it’s been tested and validated in some of the harshest and most demanding workloads of any database.

    3. High-Performance Replication at Scale

    MySQL replication offers a reliable solution for cloud applications that need to scale. Unlike other databases, MySQL’s replication capabilities provide effective data safety, making it a robust choice for applications that require high availability and durability. Additionally, MySQL enables seamless version upgrades without disrupting operations, ensuring the system always has the latest features and security patches. The read scaling feature of MySQL improves performance by distributing the read load across multiple instances, making it ideal for large-scale cloud applications. With a proven track record at scale, MySQL replication is the optimal choice for applications that want to grow and scale efficiently.

    4. High Availability and Durability

    MySQL provides enhanced high availability and durability, ensuring that critical data is always available even during maintenance and disaster recovery. This is because MySQL is fully ACID-compliant (atomicity, consistency, isolation, durability) and provides full support for transactions. Even when the system fails, the transaction can be rolled back and the data is not lost. With NoSQL databases, data is primarily written in memory and doesn’t provide the same degree of durability or consistency.

    5. Ease of Implementation and Debugging

    MySQL is easy to install, implement and debug compared to NoSQL. MySQL is supported by a large community of developers and database administrators who use it for a diverse range of applications. MySQL is also open-source and free to use, making it a great choice for businesses of all sizes. NoSQL systems require the installation of additional tools, libraries, and other components for implementation, making it more complex and time-consuming.

    MySQL provides many benefits for developers of high-scale cloud applications, ranging from its powerful SQL language for complex querying to its high availability and flexibility for managing multi-table joins. NoSQL remains a viable option in some cases, but developers who are building high-scale cloud applications are mainly sticking with MySQL due to its scalable and reliable nature, easy implementation and flexible query-handling capabilities. Choosing the right database engine is critical for any organization that relies heavily on large and data-heavy applications. MySQL continues to stand the test of time when it comes to ensuring performance and getting consistent results.

  • The Database of the Future: Seven Key Principles

    The Database of the Future: Seven Key Principles

    The database of the future will be more than just a database. Instead, it will be a platform that focuses on the user experience and abstracts the technology. Looking at the evolution of application development, an enormous amount of effort has made it easier to build and deploy applications. Similarly, databases need to evolve for ease of use with a delightful developer experience and an exemplary user interface that surfaces features and functionalities that engineers will actually use.

    Here are seven principal features needed to chart the development of the future database.

    1. Serverless by Default

    Serverless is unquestionably the most significant paradigm shift in software engineering in the last five years and the one that’s been realized the least. There aren’t that many people at this point that are all in on serverless. It’s the shift away from buying a server to a service that does what you need and scales with your growth.

    Serverless by default is the only way to ensure the database of the future will be easy to operate while being consistently reliable. Serverless is evolving from running functions in the cloud to becoming the standard for fast-paced development teams that don’t want to worry about vCPUs or node pools but focus on outcomes.

    The companies that are doing it the best still deploy servers, but they are leveraging products that scale independently, regardless of how many servers they have. Their component vendors can increase the number of resources allotted to them, and they only pay for what they use, and the architecture of the solution scales in that way. They’re not buying a single server and pushing it as hard as they can. They’re telling one platform, ‘here’s my code,’ they’re telling another, ‘here’s my data,’ and then that scales up based on usage much, much farther than buying a single server.

    When people think serverless, they think JavaScript and Lambda, but there’s serverless PHP out there, too. It’s not just the JavaScript community. Other software paradigms are going for this. We will see more and more people pulling this out when they need to do some quick code and they want to ship to production as quickly as possible and scale as quickly as possible.

    2. Easy to Operate

    The most significant advancements in DevOps have been freeing developers from complex operations that overwhelm their day-to-day operations. Engineering teams today are organized around product and business goals, not maintenance and servicing. But databases have yet to catch up. Product teams still rely on experts to perform overly complicated database operations tasks.

    The database of the future must fit into everyone’s DevOps workflows. It must be usable for any developer and leveraged by every team within a technical organization. The database needs to be operable by everyone and no longer require database admins to manage backups and capacity planning or worry about disaster recovery.

    Developer-centric features like database branching, database developer environments, autoscaling and usage-based billing will be commonplace.

    3. Reliable

    Reliable simply means it’s harder to hit the scaling limits. Not only does it mean that the database is there, but that you get the right information when something is going wrong, and you can collaboratively help scale.

    Nothing scales infinitely. There are not enough computers in the world to scale something to infinity. You’ll always be able to query a database and pull too much information out of it too fast. No matter how many cars you get or how much horsepower you have, you can’t go a million miles an hour. A good database must let you know when you’re hitting those limitations and help you move past them, whether at a small scale, medium scale or large scale.

    4. Interoperable

    Future databases will be accessible to every imaginable client–from smart refrigerators to fleets of autonomous delivery vehicles. But this client-agnostic approach requires planning for many more transactions and connections than most current databases could ever manage simultaneously.

    In the future, databases can handle unlimited connections through smart connection pooling, query replication and intelligent query routing. Databases will also need to serve a wide set of connections and clients. Although we are already seeing many databases offering web APIs and new connection types, as these get tested at scale, we will begin to see them adopted and used to power the next generation of applications.

    5. Globally Distributed, Locally Available

    Today, most businesses and applications don’t need a global database, which often introduces unnecessary complexity and operating costs. However, there are many reasons the future database will need to be globally distributed, as they must be located where you need them the most.

    The key to this is knowing what your requirements are. Many people look at multi-region and think it’s faster reads, failover, scaling and breaking the speed of light. Ultimately, it’s all a series of tradeoffs. For example, when you read from a local replica, you trade off consistency because you have asynchronous replication. But this is really leveraging the global internet to deliver a better outcome where it’s necessary.

    Being compliance-ready with regionally stored data enables you to scale rapidly to a new region and provides a great user experience by quickly serving locally available data. High-transaction, low-latency applications such as mobile games already need this capability.

    But there’s one caveat: Global data distribution cannot break principle number two—being easy to operate. Tools will need to be elegant and have straightforward interfaces as their main goal is to make operations easier, not harder.

    6. Intelligent

    The future database is intended to be used by people and will be able to tell them how it needs to be used and how to make it better. All the tools you buy today can only give you the data you need to make some educated guesses. The future database will replace that with concrete recommendations, then self-healing actions.

    This starts with basic data collection and observability and moves to, “let’s record every query that someone makes and use some decision engines and some AI and recommend how they can shard automatically.” It will be able to say, “I’ve recorded your database use for the last 30 days; this is how you should shard for optimal performance. Click the button, and we’ll do it.”

    The future database will say, “You’re scaling too far for the single machine at a per-user level. You must break it down into two or break it down into four, and we figured out how to do it for you, so you don’t have to figure that out. We’ve sharded your data on your behalf.”

    7. Linearly Horizontally Scalable

    Future databases will also need to be designed for future scale. Only a handful of companies on the planet have hit a scale that tests the limits of current technologies, but as information grows, more companies will get there. The next databases will do that by automatically scaling both vertically and horizontally within seconds. Many existing databases require a maintenance window, replication and a failover before they can be scaled up or out. But downtime is unacceptable, and scale should not come at the cost of performance. And it doesn’t have to. The database of the future will scale intelligently and without a blip on the status page.

    In short, the consumer should be able to get what they need when they need it, with no risks. It should be easy to say, “I’ve doubled the number of servers, I’ve doubled the amount of throughput. I’ve quadrupled the number of servers and the amount of throughput.” This is what sharding provides. Good sharding happens automatically at a super high scale, and you’ll only pay for what you use as you go along. The future database will do all of this without users having to turn a knob.

    In conclusion

    It will take the entire database industry to agree on these principal features, adopt a user-focused approach and build future database platforms designed to make engineers more successful by delivering superior products and services to their customers. I envision a day where every company no longer worries about its infrastructure and can simply focus on its business. I want development teams to take back control over their development workflow. Using a database should be as easy as writing code.