There’s a reason why every year we see a new crop of logging vendors at every developer conference, from KubeCon to AWS re:Invent. The simple truth is that logging is too time consuming, too noisy, and too expensive (often everyone’s second largest bill after their cloud bill).
In a perfect world, developers wouldn’t have to debate what data to keep and where to log events, and what tools they can afford to query them in later. It’s impossible to predict what data will be needed in the future, and these decisions are taking up unnecessary time in the development process.
There’s a concept called “Logging FOMO” where engineers add tons of log lines throughout their code, because they are worried that when something goes wrong, they won’t have the appropriate logs to help troubleshoot the issue. In other words, engineers are proactively preparing for the what-ifs: What if I need more data for my APM? What If I won’t be able to understand what is happening? What if someone else needs this data point? What if in the future, this product will do something different? What if I forget how this code works? What if I’ll need to add another feature here? What if someone hacks into the network and I need to find out when they got in and what they did?
These are legitimate concerns. But there are trade-offs with traditional logging, from performance to cost, that make it one of the worst parts of the job as a developer. These log lines often compromise a large part of the pull requests we perform each day, and can become so noisy as to almost be meaningless—if everything is important, nothing is.
There must be a better way.
Logging Re-Imagined with Axiom
The companies that will win in the AI age will leverage as much of that data and context as possible. Data is the lifeblood of reliable AI – and that’s where Axiom comes in. Axiom reinvents log management for high-scale engineering teams by avoiding data gymnastics like sampling or the debate over which tool can store the data long term. With Axiom’s ultra-efficient block format on object storage, businesses are empowered to keep all of their data and query it on demand.
On top of that, Axiom intelligently unifies logs and distributed traces in the same database, providing unprecedented visibility and control. Built-in data routing capabilities ensure freedom from vendor lock-in, and our thoughtful approach to ingest, storage, and query leverages the best of cloud technology to deliver unmatched performance and cost-effectiveness.
Key Features of Axiom Include
Log management for high-scale engineering
Centralize, analyze, and control all your log data with unprecedented efficiency and cost-effectiveness.
Unify observability with built-in distributed tracing
Seamlessly integrate logs and traces for comprehensive system visibility and faster problem resolution.
Break free from vendor lock-in with built-in data routing
Process logs at rest and in motion, ensuring complete control and flexibility over your data.
Future-proof your log management with cloud-native architecture
Leverage the best of cloud technology for unparalleled scalability, performance, and cost optimization.
Logging in the Age of AI
Modern systems generate tons of data daily, mostly log data. The data created worldwide is forecasted to reach 181 zettabytes by 2025. These logs' increasing scale and complexity make traditional and manual inspection and analysis time-consuming and ineffective.
But just as a house needs a strong foundation, AI systems require accurate and comprehensive data to learn patterns and make informed predictions. Inaccurate or incomplete data can misguide AI algorithms, leading to flawed conclusions and unreliable outputs.
Conferences these days are full of users looking to log everything they need, and trying to figure out how they can afford to do so while weighing security, reliability, and risk management. Many are building in-house solutions for long-term storage in S3 without compression, without querable data, just a place to dump data so they can get back to it someday if they ever happen to need it. This is where Axiom comes in.
With Axiom’s centralized datastore, high-scale engineering organizations don’t have to compromise on what to keep, what to keep warm (always querable), or where to store data. Feed it all in, and keep it all—because you can afford to. Meanwhile you can flow data out to other destinations for specific use-cases (SIEM for example). Axiom, at scale, is the solution to the nagging logging problems plaguing the cloud era.
