The database landscape evolves rapidly and often in unexpected directions. The era of relying solely on a single SQL database to run a business is a thing of the past. We've embraced NoSQL solutions, then shifted toward hybrid databases combining SQL and NoSQL features. Meanwhile, hosting has transitioned from on-premise setups to cloud and even serverless architectures.
Keeping pace with these advancements becomes even more challenging when machine learning and AI enter the equation. Companies that fail to adopt AI risk falling behind, wasting resources on outdated solutions, and missing out on the automation and efficiency AI can offer. If you're a C-level executive looking to elevate your business, read on to discover how AI can revolutionize observability.
Turn Your Observability Into Understanding
Slow databases can have a significant negative impact on your business. Outages caused by poor performance can lead to downtime, disrupting operations, incurring financial losses, and harming your company's reputation. Additionally, slow access to critical information hampers employee productivity, leading to inefficiencies and delays. To ensure smooth operations, maintaining an optimized database is crucial for accurate, reliable, and readily available data.
Over the years, we've taken considerable strides in improving database health. It began with telemetry, enabling the collection of signals. We extended this by embedding telemetry throughout our pipelines to gain visibility into key metrics. Application performance monitoring solutions followed, allowing us to track these metrics and receive alerts when performance starts to decline.
Today, however, we need to go beyond just monitoring and alerting. It’s no longer enough to collect signals and react to threshold breaches. We must understand how different components interact, how they impact the user experience, and proactively prevent issues before they occur. This is where AI excels, enabling businesses to deliver faster, smarter solutions with unprecedented efficiency.
Boost Database Performance
Empowering teams to work efficiently requires providing tools that reduce the likelihood of errors. This involves carefully analyzing queries, schema migrations, indexes, configurations, and all aspects of database management.
Understanding the performance of your queries before they reach production is vital. Metis enables developers to analyze queries and configurations, offering a clear view of how proposed changes will affect production environments. Beyond analysis, Metis delivers actionable insights to help identify issues and optimize performance, ensuring smoother and more effective database operations.
Metis uses AI to provide even more insights and suggestions:
This way we can see how things interact with each other and prevent performance issues before even deploying to production.
Improve Database Schemas
Schema migrations carry the risk of data loss, making it essential to address this proactively. Metis evaluates your schema migrations to determine their potential impact on your production database, ensuring protection against data loss and performance degradation.
We can use AI to improve indexing and schemas to gain even more performance benefits:
We can make our databases faster and tune them according to our business needs instead of some raw monitoring metrics.
Use Metis and Don’t Miss Out
AI has the potential to significantly enhance your databases and observability, allowing you to elevate your monitoring solutions and ensure database reliability tailored to your unique business requirements.
