Nobl9, the service level
observability company, recently announced Replay, a new set of capabilities to its
Service Level Objective (SLO) platform. The new features allow enterprises to
create automated SLOs from day one with historical data from the previous
thirty days and pre-calculated error budgets. VMblog caught up with Kit Merker,
COO of Nobl9, to discuss these new capabilities.
VMblog: To kick things off, please
give me an update on Nobl9 and the platform.
Kit Merker: The Nobl9 SLO Platform helps
organizations use SLOs to accelerate software delivery by adding business
context and eliminating data overload. Our customers today include enterprises
in the financial services, e-commerce, and SaaS industries that use Nobl9 to
accelerate engineering, set clear software reliability goals, and ensure
end-user satisfaction. The platform now integrates with dozens of popular
monitoring systems, such as Amazon Managed Prometheus, AppDynamics, New Relic,
and Google Cloud Monitoring, to collect metrics that are measured against
business-justified reliability targets so teams can deliver software
efficiently. Nobl9 helps software and business teams deliver reliable features
faster and at a reasonable cost.
VMblog: Tell me about Nobl9 Replay
which you announced today.
Merker: Nobl9 Replay is a huge productivity
advancement, cutting time to value on SLOs from weeks to minutes. Replay lets
customers instantly import up to thirty days of reliability metrics when they
define their SLOs. Their historical Service Level Indicator (SLI) data is
retrieved alongside real-time observability metrics so you can start collecting
and tuning SLOs immediately. With Replay, Nobl9 enables automation to capture
historical data, combine them with real-time SLI data, and allow customers to
view SLO charts and automate various workflows based on SLOs-at-risk.
VMblog: Why is this important?
Merker: In a word, productivity. Everyone
needs to do much more with less these days, and automation is the key to
productivity. Instead of watching charts or responding to endless unactionable
alerts, SLOs make operations more efficient so you can get back to the real
work. Replay is a booster on the iteration and lifecycle of defining SLOs -
which means better understanding your service and your customers and taking
direct action to deliver value to them.
VMblog: What data sources does Replay
pull in?
Merker: Replay currently supports Datadog,
Prometheus, Amazon Managed Prometheus, Graphite, and Splunk metrics. We plan to
add Replay functionality to all 24+ existing data sources very soon.
VMblog: Is there anything else you'd
like to share with our readers about SLOs and Nobl9?
Merker: Technology executives are looking for
ways to gain an edge and eliminate waste. The Nobl9 SLO Platform lets
technology executives look at their engineering culture and system holistically
by providing a central system of record for service ownership, reliability
goals, and the historical track record of service health. The platform gives a
strategic view of how to run services best to handle fundamental tradeoffs:
speed of delivery vs. technical debt, observability data overload vs.
actionable insights, and resiliency vs. redundant infrastructure cost.
Because
SLOs make operations efficient (whether you call it SRE, platform engineering, DevOps,
or something else), SLO adoption is growing to gain visibility, improve
decisions, and protect businesses from disruptions. In a recent survey by Nobl9 and Dimensional
Research, 8 out of 10 companies surveyed are increasing their use to provide
greater visibility into new technologies and improve their performance. But
increasingly, business teams across the enterprise in manufacturing, R&D,
marketing, and finance are also employing SLOs to map directly to business
operations and improve decision-making.
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