# How we reached 99.9% uptime during our busiest season

DevFeed: [How we reached 99.9% uptime during our busiest season](<https://devfeed.tech/articles/how-we-reached-99-9-uptime-during-our-busiest-season-31922.md>)

Original publisher: [Read original article](<http://engineering.remind.com/99-uptime-busiest-season/>)

Author: Remind

Published: 2020-02-20T00:00:00Z

Content type: article

Language: en

Sources: [Remind](<https://devfeed.tech/sources/remind.md>)

Topics: [Availability](<https://devfeed.tech/topics/availability.md>), [autoscaling](<https://devfeed.tech/topics/autoscaling.md>), [App](<https://devfeed.tech/topics/app.md>), [systems](<https://devfeed.tech/topics/systems.md>), [cpu](<https://devfeed.tech/topics/cpu.md>)

Tags: [app](<https://devfeed.tech/tags/app.md>), [autoscaling](<https://devfeed.tech/tags/autoscaling.md>), [availability](<https://devfeed.tech/tags/availability.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [latency](<https://devfeed.tech/tags/latency.md>), [systems](<https://devfeed.tech/tags/systems.md>)

## AI overview

Remind describes how it improved availability during the back-to-school season by measuring downtime, establishing and tightening uptime SLAs, and adopting autoscaled systems. Reported downtime fell from more than 1,000 minutes in August and September 2018 to 80 minutes in 2019.

## Source excerpt

Availability is the lifeblood of any app. Downtime blocks new users from signing up, it damages the company reputation, and so on. Additionally for Remind, serving education administrators as they work to increase engagement of entire communities further drives the need for our systems to be available. While administrators share many of the same expectations that teachers have of Remind, that ultimate responsibility to their communities make it crucial for administrators to know that their messages were delivered and that delivery was timely. The impact of downtime is most apparent during the back-to-school season. Because Remind usage is so closely tied to the school year, we see our traffic increase 5 times and our sign-ups increase 15 times between July 1st and September 30th each year. As a result, we are always looking for ways to improve our availability. First, we need to be able to measure it. Internally, we define downtime at Remind as an error rate over 5%. When we first set out to measure our availability 2 years ago, the first step was to establish an internal uptime Service Level Agreement, or SLA. Once we established a baseline, we prioritized work to help us conform to that SLA. And once we met that SLA, we optimized them to be even tighter. We have integrated the cycle of honing our targets and tuning our systems to meet those targets into our product delivery cadence. This investment has paid off; during back to school 2018 we had over 1000 minutes of downtime across August and September. In 2019, we reduced that to 80 minutes. Looking back, here are some tactics that enabled us to conform to progressively more aggressive SLAs at Remind. Elastic systems are more forgiving (Our original viewpoint on autoscaling systems was financially motivated. If we scale systems down at night, then we save money. This is still true, but improvements to our cost model have made the financial savings less of a motivator.) As we focused on conforming to our availabil