Weekly

Get a weekly performance report for your apps

Every Monday you see throughput, error rate and response time per app, next to the week before.

Runs: Weekly
Apps: New Relic
AI: Not needed
Access: read

Send this to your assistant

Create a ClickRuntime automation: every Monday at 9am email me last week's throughput, error rate and average response time for each of my New Relic apps, compared with the previous week.

Paste it into your assistant. It tells you what it will send or change before it runs live.

Add to ChatGPT Add to Claude

First time? Adding ClickRuntime to your assistant takes about two minutes.

Why use it

Why teams use this automation

Performance rarely collapses overnight. Response times creep up by 15 milliseconds with each release, an error rate rises from 0.4 to 0.9 percent after a dependency update, and throughput changes as marketing campaigns come and go. New Relic holds all of it, but looking requires opening each application and choosing a time range, so the slow drift is only noticed when a customer complains or a quarterly review asks for numbers.

Every week ClickRuntime runs an NRQL query covering the last seven days for throughput, error rate and average response time per application, runs the same query for the week before, and emails a table showing both with the change. A service that got slower stands out right away.

It is a good habit for teams who ship often and want evidence of how releases affect users.

What you get out of it

Gradual slowdowns are caught early
A response time that rises each week shows up as a trend in the email. You investigate while the cause is one or two releases back, not after fifteen of them.
Releases are judged by their effect
Seeing error rate before and after the week of a big deploy gives a factual view of its impact. The team learns which kinds of changes tend to hurt performance.
One table covers every application
Instead of opening each service in turn, you read one table with all of them. A slow internal API that nobody watched becomes visible next to the customer-facing site. A slow internal API that nobody watched becomes visible beside the customer-facing site.
Conversations with leadership have numbers
When someone asks whether the platform got faster, you point to weeks of throughput and latency. Budget requests for performance work can be supported with the data. Budget requests for performance work can then be backed by weeks of data, not impressions.
Capacity decisions follow demand
Throughput by week shows growth that will need more instances before the next peak. You scale ahead of load, not during an incident. You add instances ahead of the next seasonal peak instead of reacting during an incident, and you can show why.

How it works

What happens, step by step

Every Monday, ClickRuntime looks up the last seven days of New Relic data for each of your apps.
It measures requests per minute, error rate and average response time, and gets the same figures for the week before.
You get one email with a line per app showing this week next to last week, like "412 rpm (was 388)".

Before it runs live

Connect New Relic

What you get

RunsWeekly

Get a weekly performance report for your appstoday, 9:00Succeeded

Email · Weekly app performancecheckout-api: 412 rpm (was 388), errors 0.41% (was 0.62%), 182 ms (was 201 ms)

Build your own

Need it to work differently?

This template is a starting point. Copy the prompt and change it, or describe a different automation from scratch, with your own conditions, more apps or an AI step. Your assistant writes it, tests it and runs it on ClickRuntime.

Your own rules
Conditions, thresholds, filters and exceptions, written the way you'd explain them to a colleague.
Any number of apps
One automation can read from one app and update several others. Over 248 apps are ready, and anything with an API works too.
AI where it helps
Summaries, classification, extraction and drafts use ClickRuntime's built-in AI, with no extra key.
On a schedule or on each event
Runs as often as every 5 minutes, or the moment an app sends an event, and keeps track of what it already handled.

Changes you can ask for

Run it at a different time, more or less often, or only on weekdays
Add an AI step, for example to summarize, sort or draft a reply
Add another app, for example also send it to Slack
Combine it with other New Relic steps into one automation

Under the hood

The code that runs this automation

This is the Python script that runs each time the automation starts. Your AI assistant writes it for you when you send the prompt, and you allow each step in your assistant. To change how the automation works, describe the change to your assistant and it updates the script for you. For every function it can use, see the script reference.

get_a_weekly_app_performance_report.pyexample

from clickruntime import on_trigger, credentials, http, notify

ACCOUNT_ID = 1234567
NRQL = ("SELECT rate(count(*), 1 minute) AS rpm, percentage(count(*), WHERE error IS true) AS errors, "
        "average(duration) * 1000 AS ms FROM Transaction FACET appName SINCE 1 week ago COMPARE WITH 1 week ago")

@on_trigger
def run(event):
    query = '{ actor { account(id: %d) { nrql(query: "%s") { results } } } }' % (ACCOUNT_ID, NRQL)
    resp = http.post("https://api.newrelic.com/graphql", json={"query": query},
                     headers={"API-Key": credentials.secret("NEW_RELIC_USER_KEY")})
    resp.raise_for_status()
    rows = resp.json()["data"]["actor"]["account"]["nrql"]["results"]
    by_app = {}
    for r in rows:
        by_app.setdefault(r["appName"], {})[r["comparison"]] = r
    lines = []
    for app, c in sorted(by_app.items()):
        cur, prev = c.get("current", {}), c.get("previous", {})
        lines.append(f"{app}: {cur.get('rpm', 0):.0f} rpm (was {prev.get('rpm', 0):.0f}), "
                     f"errors {cur.get('errors', 0):.2f}% (was {prev.get('errors', 0):.2f}%), "
                     f"{cur.get('ms', 0):.0f} ms (was {prev.get('ms', 0):.0f} ms)")
    notify.email_me("Weekly New Relic app performance", "\n".join(lines))
    return {"apps": len(by_app)}

FAQ

Common questions

Which metrics does it report?

Throughput, error rate and average response time by application, taken from New Relic's transaction data using NRQL. Other measures such as the 95th percentile duration can be added to the same query. Average values are shown unless you ask for percentiles.

How is the previous week compared?

The automation runs the same NRQL query for the week before and calculates the change for each application. A percentage change is shown beside each value, so trends are easy to scan. Weeks with unusual events are easy to spot because both values are shown.

Can it cover only certain applications?

Yes. Add a WHERE clause to the query, such as appName LIKE 'checkout%', or list the applications by name. You can also run separate reports for production and staging by filtering on an environment attribute.

What permissions does it need?

read. Nothing else in your accounts is used.

Does it need AI?

No. It runs without AI, so it doesn't use your plan's AI allowance.

How many runs does it use?

One run each time it runs (weekly). Checks that find nothing to do and stop right away aren't counted.

Can I change how it works?

Yes. Describe the change to your AI assistant, for example a different schedule, channel or filter. It updates the automation, tests it and tells you what changed.

Daily