Intro: Why Most Alerts Don’t Work
When everything alerts, nothing matters.
Most data teams start with good intentions—freshness checks, row counts, schema tests—but soon they’re drowning in Slack pings and PagerDuty incidents. Analysts stop reading summaries. Ops stops trusting dashboards. Engineering gets pulled into issues that aren’t theirs.
Getting this right requires two things:
- A good process for working with stakeholders and analysts to map what’s truly critical.
- A tool with the features to support it — tagging, smart alert routing, tailored communication, and summaries.
At Elementary, after working with hundreds of teams, we’ve seen what makes alerts trusted instead of ignored. We’ve helped data orgs cut noise, align on process, and route alerts in ways that actually match how their organizations are built. Out of that experience, we created a playbook.
It’s built around six strict questions:
- Why are we alerting?
- What can’t break?
- Who should know?
- When should they know it?
- Where should it live?
- How should it be communicated?
We’ll walk through this playbook using one of the most business-critical assets in any company, the orders table, to show how it works in practice.
Step 1: Why Are We Alerting on This?
Every alert adds cognitive load. If it doesn’t tie back to business value, it’s just noise.
The orders table is a great example. It powers multiple downstream assets:
- Executive KPIs: GMV, daily active orders, conversion rates.
- Marketing dashboards: ROAS, CPA, attribution models.
- Ops dashboards: order success rates, cancellations, refunds.
- Finance reporting: revenue recognition, billing accuracy.
If this table breaks, all of those assets break with it. That’s why it deserves tighter monitoring and higher-severity alerting than, say, a staging table or a lookup dimension.
In Elementary Cloud, you can tag orders as a critical asset, which automatically applies stricter monitoring and makes its downstream impact visible in the lineage graph.
Step 2: What Can’t Break About This?
The next step is defining what’s truly unacceptable to fail. This is where you move from “we test everything” to “we protect what can’t break.”
For the orders table, examples include:
- Freshness (
#technical) → the table must be updated at least once per hour, or every downstream dashboard is stale. - Primary key integrity (
#technical) →order_idmust always be unique and not null, otherwise revenue and conversion numbers are corrupted. - Schema drift (
#technical) → if someone changes or drops a column liketotal_amount, dozens of models can silently break. - Cancellation rate (
#business) → a spike >20% WoW signals a fulfillment incident and breaks funnel KPIs. - Payment method mix (
#business) → a sudden shift in card vs. PayPal could distort ROAS and checkout performance metrics. - Revenue by currency (
#business) → distribution drift could hide FX issues or market changes.
By tagging tests as #technical, #business, or even by department (e.g. #marketing, #ops), you’re defining what can’t break for each type of consumer. Tags classify the test, but routing happens later.
Step 3: Who Should Know? (Fix vs. Acknowledge)
Once you know what can’t break, the next question is: who needs to know when it does?
There are two valid approaches in Elementary:
- By owners → the alert goes to whoever wrote or owns the test (e.g. Marketing Analytics owns attribution checks, so they get the alert).
- By department tags → the alert goes to the function most impacted (e.g. all
#opstests route to fulfillment Ops, even if created by Engineering).
Both approaches make sense, and many teams use a mix depending on the asset.
From there, you separate:
- Fix responsibility → the team that must resolve the issue.
- Acknowledge responsibility → the teams that need awareness, since their dashboards or KPIs may be unreliable.
Orders examples:
This way, Elementary alert rules can mirror how your org actually works — either following ownership or following department responsibility — while always distinguishing between who fixes and who acknowledges.
Tip: Elementary also supports subscribers, so people can sign up to be alerted on specific tests. This is especially useful for analysts who care about one or two metrics but don’t need to be included in broader alert routing.
Step 4: When Should They Know?
Urgency depends on responsibility:
- Fix alerts → real-time, often PagerDuty or direct Slack ping.
- Acknowledge alerts → Can be grouped into daily or weekly summaries, so business users stay informed without being spammed.
Orders examples:
Step 5: Where Should Alerts Live?
The channel matters as much as the timing.
- Fix alerts: go where on-call teams already live → PagerDuty for Eng, Slack
#ops-alertsfor Ops. - Acknowledge alerts: go to channels where context is best consumed → Slack digests for analysts, daily emails for Finance, or Elementary dashboards for weekly reviews.
Orders examples:
- Freshness failure → Eng on PagerDuty, Ops in Slack FYI.
- Cancellation spike → Ops in
#ops-alerts, Product in Slack digest. - Revenue drift → Finance in daily email.
Elementary allows flexible routing: PagerDuty, Slack, Email, and consumer-facing summaries.
Step 6: How Should Alerts Be Communicated?
Even the best-routed alert will be ignored if it’s incomprehensible.
- Fix alerts need technical context: failed rows, test metadata, lineage. Example: “Orders table freshness 2h late. Downstream: ROAS, GMV. Last row at 08:02 UTC.”
- Acknowledge alerts need plain, business-friendly language: “Cancellation rate spiked 20% yesterday. Ops is investigating. Dashboards impacted: Conversion Funnel, ROAS.”
Elementary lets you define consumer-friendly alert templates so engineers get debugging details, while business teams get short messages they actually read.
Step 7: Summaries, Audits, and Noise Reduction
The biggest reason alerts fail is volume. When dozens fire every hour, teams ignore them. Reducing noise means two things:
- Summaries & grouping: bundle alerts into Slack digests or daily emails so people see trends without constant interruption.
- Audit & learn: regularly review which alerts led to action, which were acknowledged but not useful, and which were ignored. The goal is to cut out what’s not actionable and refine thresholds so alerts stay sharp.
At Elementary, we’ve seen this transform alerting culture: instead of constant firefighting, teams trust that the alerts they do get are the ones that matter.
Example Routing Rules in Practice
Conclusion
Alert fatigue isn’t solved by adding more tests — it’s solved by designing alerts that reflect how your organization is built.
And getting there is always a combination of process and tooling:
- Process → working with stakeholders to define what can’t break and who needs to know.
- Tooling → using Elementary to tag, route, group, and tailor alerts so they’re actionable and understandable.
With this approach, alerts stop being noise and start being a living contract between data and the business. They don’t just say something broke — they tell the right people, at the right time, in the right way, so the business can move forward with trust.
Intro: Why Most Alerts Don’t Work
When everything alerts, nothing matters.
Most data teams start with good intentions—freshness checks, row counts, schema tests—but soon they’re drowning in Slack pings and PagerDuty incidents. Analysts stop reading summaries. Ops stops trusting dashboards. Engineering gets pulled into issues that aren’t theirs.
Getting this right requires two things:
- A good process for working with stakeholders and analysts to map what’s truly critical.
- A tool with the features to support it — tagging, smart alert routing, tailored communication, and summaries.
At Elementary, after working with hundreds of teams, we’ve seen what makes alerts trusted instead of ignored. We’ve helped data orgs cut noise, align on process, and route alerts in ways that actually match how their organizations are built. Out of that experience, we created a playbook.
It’s built around six strict questions:
- Why are we alerting?
- What can’t break?
- Who should know?
- When should they know it?
- Where should it live?
- How should it be communicated?
We’ll walk through this playbook using one of the most business-critical assets in any company, the orders table, to show how it works in practice.
Step 1: Why Are We Alerting on This?
Every alert adds cognitive load. If it doesn’t tie back to business value, it’s just noise.
The orders table is a great example. It powers multiple downstream assets:
- Executive KPIs: GMV, daily active orders, conversion rates.
- Marketing dashboards: ROAS, CPA, attribution models.
- Ops dashboards: order success rates, cancellations, refunds.
- Finance reporting: revenue recognition, billing accuracy.
If this table breaks, all of those assets break with it. That’s why it deserves tighter monitoring and higher-severity alerting than, say, a staging table or a lookup dimension.
In Elementary Cloud, you can tag orders as a critical asset, which automatically applies stricter monitoring and makes its downstream impact visible in the lineage graph.
Step 2: What Can’t Break About This?
The next step is defining what’s truly unacceptable to fail. This is where you move from “we test everything” to “we protect what can’t break.”
For the orders table, examples include:
- Freshness (
#technical) → the table must be updated at least once per hour, or every downstream dashboard is stale. - Primary key integrity (
#technical) →order_idmust always be unique and not null, otherwise revenue and conversion numbers are corrupted. - Schema drift (
#technical) → if someone changes or drops a column liketotal_amount, dozens of models can silently break. - Cancellation rate (
#business) → a spike >20% WoW signals a fulfillment incident and breaks funnel KPIs. - Payment method mix (
#business) → a sudden shift in card vs. PayPal could distort ROAS and checkout performance metrics. - Revenue by currency (
#business) → distribution drift could hide FX issues or market changes.
By tagging tests as #technical, #business, or even by department (e.g. #marketing, #ops), you’re defining what can’t break for each type of consumer. Tags classify the test, but routing happens later.
Step 3: Who Should Know? (Fix vs. Acknowledge)
Once you know what can’t break, the next question is: who needs to know when it does?
There are two valid approaches in Elementary:
- By owners → the alert goes to whoever wrote or owns the test (e.g. Marketing Analytics owns attribution checks, so they get the alert).
- By department tags → the alert goes to the function most impacted (e.g. all
#opstests route to fulfillment Ops, even if created by Engineering).
Both approaches make sense, and many teams use a mix depending on the asset.
From there, you separate:
- Fix responsibility → the team that must resolve the issue.
- Acknowledge responsibility → the teams that need awareness, since their dashboards or KPIs may be unreliable.
Orders examples:
This way, Elementary alert rules can mirror how your org actually works — either following ownership or following department responsibility — while always distinguishing between who fixes and who acknowledges.
Tip: Elementary also supports subscribers, so people can sign up to be alerted on specific tests. This is especially useful for analysts who care about one or two metrics but don’t need to be included in broader alert routing.
Step 4: When Should They Know?
Urgency depends on responsibility:
- Fix alerts → real-time, often PagerDuty or direct Slack ping.
- Acknowledge alerts → Can be grouped into daily or weekly summaries, so business users stay informed without being spammed.
Orders examples:
Step 5: Where Should Alerts Live?
The channel matters as much as the timing.
- Fix alerts: go where on-call teams already live → PagerDuty for Eng, Slack
#ops-alertsfor Ops. - Acknowledge alerts: go to channels where context is best consumed → Slack digests for analysts, daily emails for Finance, or Elementary dashboards for weekly reviews.
Orders examples:
- Freshness failure → Eng on PagerDuty, Ops in Slack FYI.
- Cancellation spike → Ops in
#ops-alerts, Product in Slack digest. - Revenue drift → Finance in daily email.
Elementary allows flexible routing: PagerDuty, Slack, Email, and consumer-facing summaries.
Step 6: How Should Alerts Be Communicated?
Even the best-routed alert will be ignored if it’s incomprehensible.
- Fix alerts need technical context: failed rows, test metadata, lineage. Example: “Orders table freshness 2h late. Downstream: ROAS, GMV. Last row at 08:02 UTC.”
- Acknowledge alerts need plain, business-friendly language: “Cancellation rate spiked 20% yesterday. Ops is investigating. Dashboards impacted: Conversion Funnel, ROAS.”
Elementary lets you define consumer-friendly alert templates so engineers get debugging details, while business teams get short messages they actually read.
Step 7: Summaries, Audits, and Noise Reduction
The biggest reason alerts fail is volume. When dozens fire every hour, teams ignore them. Reducing noise means two things:
- Summaries & grouping: bundle alerts into Slack digests or daily emails so people see trends without constant interruption.
- Audit & learn: regularly review which alerts led to action, which were acknowledged but not useful, and which were ignored. The goal is to cut out what’s not actionable and refine thresholds so alerts stay sharp.
At Elementary, we’ve seen this transform alerting culture: instead of constant firefighting, teams trust that the alerts they do get are the ones that matter.
Example Routing Rules in Practice
Conclusion
Alert fatigue isn’t solved by adding more tests — it’s solved by designing alerts that reflect how your organization is built.
And getting there is always a combination of process and tooling:
- Process → working with stakeholders to define what can’t break and who needs to know.
- Tooling → using Elementary to tag, route, group, and tailor alerts so they’re actionable and understandable.
With this approach, alerts stop being noise and start being a living contract between data and the business. They don’t just say something broke — they tell the right people, at the right time, in the right way, so the business can move forward with trust.
