As our growth has accelerated over the past few quarters, we’ve gained additional insights into what customers care about and why they choose us for machine data analytics. In addition, our integrations and partnerships with Akamai, Amazon Web Services and ServiceNow have provided even more context around what customers investing in cloud services want and need. I thought it would be instructive to share one perspective on what we’ve learned.
- Our cloud-native strategy is an asset, not just because of traditional TCO and elasticity reasons but because the fundamental cost of running a high-volume, cloud-based log management service that automatically detects patterns and anomalies is prohibitively expensive for customers choosing an on-premise alternative. It goes back to a central point that many customers bring up with us – “we want to be users of the system, not administrators of it.”
- Our customers really care about Service Level Agreements. Traditional SLAs focus on uptime/availability. This is essential, but not always sufficient. We’ve found that as a cloud provider in this space it’s also necessary to provide a SLA for query performance. Why? It’s quite simple. Query performance is essential to delivering on the promise of time-to-value, not just around initial setup, but also around ongoing operations.
- My colleagues have previously discussed the rationale behind LogReduce and Anomaly Detection. One of the tenets of our product strategy is that the rate of growth of machine data has far outpaced the ability for human rules to automatically capture all insights in your logs. We thus need to combine machine learning with human knowledge to uncover both known and unknown events in machine data. This combination and the reason we invest so much in data science is the underpinning of our analytics strategy.
- Log data is “inherently” chatty and volumes spike when issues arise or seasonality goes beyond the norm. It’s during these periods that the need to instantly burst capacity to meet customer demand is critical. An on-premise environment cannot by definition get this done without having expensive spare capacity sitting around, a situation most organizations don’t typically provision for. It’s why we’ve incorporated elastic bursting to over 5x of your regular volume as part of our regular service.
These and other differentiators are a significant reason why we’ve grown by 500% over the past year. We decided to take these differentiators and our other capabilities and make this part of our website. Enjoy the read and understand where we’re focusing our R&D efforts to create a valuable machine data analytics service.