Platform observability and SLAs in MLOps - Step-by-Step Execution

Process Flow - Platform observability and SLAs

Start Monitoring

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Collect Metrics & Logs

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Analyze Data

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Detect Anomalies or Issues

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Compare with SLA Targets

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Trigger Alerts if SLA Violated

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Take Remediation Actions

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Report SLA Compliance

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End Cycle / Continuous Monitoring

This flow shows how platform observability collects data, checks it against SLAs, triggers alerts, and reports compliance continuously.

Execution Sample

MLOps

metrics = collect_metrics()
logs = collect_logs()
anomalies = analyze(metrics, logs)
if anomalies > threshold:
    alert('SLA violation')
report_sla_status()

This code collects metrics and logs, analyzes them for anomalies, alerts if SLA is violated, and reports the status.

Process Table

Step	Action	Data State	Condition	Result
1	Collect metrics	metrics={'cpu': 70%, 'latency': 120ms}	N/A	Metrics collected
2	Collect logs	logs=['error1', 'error2']	N/A	Logs collected
3	Analyze data	anomalies=2	N/A	Anomalies counted
4	Check anomalies > threshold	threshold=1	2 > 1	True - SLA violation detected
5	Trigger alert	alert sent	N/A	Alert sent to ops team
6	Report SLA status	SLA status=violation	N/A	SLA violation reported
7	End cycle	N/A	N/A	Monitoring cycle complete

💡 Monitoring cycle ends after reporting SLA status and alerting if violation detected

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	Final
metrics	{}	{'cpu': 70%, 'latency': 120ms}	{'cpu': 70%, 'latency': 120ms}	{'cpu': 70%, 'latency': 120ms}	{'cpu': 70%, 'latency': 120ms}	{'cpu': 70%, 'latency': 120ms}	{'cpu': 70%, 'latency': 120ms}
logs	[]	[]	['error1', 'error2']	['error1', 'error2']	['error1', 'error2']	['error1', 'error2']	['error1', 'error2']
anomalies	0	0	0	2	2	2	2
alert	None	None	None	None	sent	sent	sent
SLA status	unknown	unknown	unknown	unknown	violation	violation	violation

Key Moments - 3 Insights

Why do we check if anomalies > threshold before alerting?

We compare anomalies to the threshold to decide if the SLA is violated. Step 4 in the execution_table shows this condition check. Alerting only happens if this condition is true to avoid false alarms.

What happens if no anomalies are detected?

If anomalies are not greater than the threshold, the alert is not triggered and SLA status remains compliant. This is implied by the condition in Step 4 and the absence of alert in Step 5.

Why do we collect both metrics and logs?

Metrics give numeric performance data, logs provide detailed event info. Together they help analyze platform health better, as shown in Steps 1 and 2 where both are collected before analysis.

Visual Quiz - 3 Questions

Look at the execution_table at Step 4. What is the condition checked?

A anomalies > threshold

B metrics > threshold

C logs contain errors

D alert sent

💡 Hint

Check the 'Condition' column in Step 4 of the execution_table

At which step is the alert triggered according to the execution_table?

A Step 3

B Step 4

C Step 5

D Step 6

💡 Hint

Look at the 'Action' column to find when alert is sent

If anomalies were 0, how would the SLA status change in the variable_tracker?

A It would remain 'violation'

B It would change to 'compliant'

C It would be 'unknown'

D It would trigger an alert

💡 Hint

Refer to the 'anomalies' and 'SLA status' rows in variable_tracker

Concept Snapshot

Platform observability means collecting metrics and logs continuously.
Analyze this data to detect anomalies.
Compare anomalies against SLA thresholds.
If threshold exceeded, trigger alerts and report SLA violation.
This cycle repeats to ensure platform health and reliability.

Full Transcript

Platform observability and SLAs involve monitoring system metrics and logs to ensure the platform meets agreed service levels. The process starts by collecting metrics and logs, then analyzing them to find anomalies. If anomalies exceed a set threshold, it means the SLA is violated, so an alert is sent to the operations team. Finally, the SLA status is reported. This cycle repeats continuously to maintain platform reliability and quickly respond to issues.