Question 1

Is Grafana the same thing as Prometheus?

Accepted Answer

No. Prometheus is a time-series database and metrics collector — it scrapes endpoints, stores data, evaluates rules. Grafana is a visualization and dashboarding tool that reads from Prometheus (and 100+ other backends). They're commonly used together but each is independently useful: you can run Prometheus without Grafana (use its built-in UI for ad-hoc queries) and Grafana without Prometheus (over MySQL, CloudWatch, anything).

Question 2

How much does a Grafana / SRE / Observability engineer earn in India?

Accepted Answer

₹7-22 LPA in 2026 for mid-to-senior SRE and Platform engineers with strong Grafana + Prometheus skills. Top-tier unicorns (Razorpay, Swiggy, Zerodha, Postman, CRED, Cure.fit) pay at the upper end, especially for engineers who can design multi-tenant LGTM stacks. SRE roles are consistently among the highest-paid DevOps positions in India.

Question 3

What's the difference between Grafana, Grafana Cloud, and Grafana Enterprise?

Accepted Answer

Grafana OSS is the free open-source core — what you self-host. Grafana Enterprise is the OSS plus enterprise features (fine-grained RBAC, reporting, SLA support, premium data source plugins). Grafana Cloud is a fully-hosted SaaS offering — they run Mimir, Loki, Tempo, and Grafana for you, you just ship data in. For startups in India, Grafana Cloud's free tier (10k series, 50GB logs/month) is enough to bootstrap; mid-size companies usually self-host on EKS/GKE; only large enterprises typically take Enterprise.

Question 4

Should I learn PromQL, LogQL, or both?

Accepted Answer

Both, but PromQL first. PromQL is the lingua franca of metrics — Prometheus, Mimir, Thanos, VictoriaMetrics all speak (something close to) PromQL. Once you understand `rate()`, `sum by`, `histogram_quantile`, and joins, LogQL is a small additional step because it borrows the same selector syntax. Most SRE interviews in India spend more time on PromQL than LogQL — that's where the deep questions live.

Question 5

Is Grafana hard to learn coming from Datadog or New Relic?

Accepted Answer

The dashboard concepts (panels, variables, time ranges) transfer directly. The big shift is the query language — Datadog's tag-based query builder feels point-and-click, while PromQL/LogQL require you to write expressions. Most engineers find Grafana more powerful once they're past the PromQL learning curve (a couple of weeks of regular use). The other shift is operations: with Datadog you don't run anything, with Grafana + LGTM you do, which means understanding storage sizing, retention, and HA.

Question 6

What is Grafana and what problems does it solve?

Accepted Answer

Grafana is an open-source observability and visualization platform, originally forked from Kibana in 2014 by Torkel Ödegaard. It solves the problem of a unified pane of glass over many different telemetry backends. Before Grafana, teams had one UI for Prometheus, another for ElasticSearch logs, a third for CloudWatch — switching between them on incident calls was brutal. Grafana connects to 100+ data sources (Prometheus, Loki, Tempo, Mimir, MySQL, PostgreSQL, CloudWatch, Elasticsearch, Datadog, etc.) and lets you build dashboards, alerts, and exploration views over all of them in one place. In 2026, Grafana Labs has bundled their LGTM stack — Loki (logs), Grafana (dashboards), Tempo (traces), Mimir (metrics at scale) — making it the dominant open-source observability story. Companies use it for application performance monitoring, infrastructure dashboards, business KPIs, and on-call alerting.

Question 7

What is a dashboard and what is a panel in Grafana?

Accepted Answer

A dashboard is a single page that groups related visualizations together — for example, an 'API latency' dashboard for a service or a 'Kubernetes node health' dashboard for a cluster. Each visualization on the dashboard is a panel. A panel has its own query (against a data source), a visualization type (time series, gauge, stat, bar chart, table, heatmap, etc.), and display options. Panels can be arranged in rows for grouping, resized via drag-handles, and given variables that change what they show. Dashboards are stored as JSON, can be version-controlled in git, and are imported/exported as JSON files (or via the new file-based provisioning in Grafana 11). Dashboards also support time-range selection at the top — the chosen range is passed to every panel's query automatically.

Question 8

What is a data source in Grafana?

Accepted Answer

A data source is a connection to a backend that holds telemetry — Prometheus, Loki, Tempo, MySQL, CloudWatch, Elasticsearch, and so on. Grafana itself stores almost nothing about your metrics; it queries the data source at render time and visualizes the response. You configure data sources at the Grafana org/instance level (Connections → Data sources), and every panel picks one. Each data source has its own query editor — PromQL for Prometheus, LogQL for Loki, SQL for relational DBs. In production, never click-configure data sources in the UI for a real environment — use provisioning files (YAML in `/etc/grafana/provisioning/datasources/`) so they're reproducible across environments and survive a reinstall.

Question 9

What is PromQL and how do you write a basic query?

Accepted Answer

PromQL (Prometheus Query Language) is the query language for Prometheus and Mimir. It operates on time-series data — every metric is a (name, labels, value, timestamp) tuple. The basic building blocks: an instant vector selector picks one value per series at the current time (`http_requests_total{status='200'}`), a range vector selector picks a window (`http_requests_total[5m]`), and functions like `rate()`, `sum()`, `avg()` aggregate across series and time. The most common pattern in dashboards is `rate()` over a range vector wrapped in `sum() by (...)`. The trap most beginners hit: you can't graph a counter directly — counters always increase, so you must apply `rate()` or `increase()` to get something meaningful.

Question 10

What is LogQL and how is it different from PromQL?

Accepted Answer

LogQL is Loki's query language, designed to feel similar to PromQL but for logs. A LogQL query has two parts: a log stream selector with label matchers (just like PromQL), followed by an optional filter expression. Selectors pick streams by labels (`{app='api',env='prod'}`), filters narrow lines (`|= 'error'`, `!= 'health-check'`, `|~ 'regex'`). LogQL also has metric queries that turn log lines into time series — `rate({app='api'} |= 'error' [5m])` gives errors per second. Key gotcha: Loki indexes only labels, not log content. Stuffing high-cardinality fields (request_id, user_id) into labels destroys Loki performance — keep those in the log line and filter with `|=` or extract on the fly with `| json`.

Question 11

What is MetricsQL and when does it come up?

Accepted Answer

MetricsQL is the query language used by VictoriaMetrics, a popular Prometheus-compatible TSDB. It's a strict superset of PromQL — every PromQL query runs unchanged, but MetricsQL adds extra functions (`keep_last_value`, `running_sum`, `alias`, default values for missing series, friendlier `WITH` template expressions). It comes up when you're interviewing at a company that's swapped Prometheus for VictoriaMetrics to save infra cost (about 10× less RAM and disk for the same metrics in many benchmarks). In Grafana, you point a Prometheus-type data source at VictoriaMetrics's URL and queries 'just work', but enabling the VictoriaMetrics datasource plugin unlocks the MetricsQL-specific extensions.

Question 12

What are dashboard variables and why are they useful?

Accepted Answer

Variables (also called template variables) are dropdowns at the top of a dashboard that let you parameterize panel queries — pick an environment, a service, a pod, a customer — and every panel updates. Without variables, you'd build one dashboard per service or per cluster, which doesn't scale. Common types: Query (populated from a data source — `label_values(up, job)` to get all job names from Prometheus), Custom (hardcoded values), Constant, Data source (switch the data source itself), Ad hoc filters (add arbitrary label filters that apply globally). The variable is referenced in queries as `$varname` or `${varname}`. Variables support 'All' (`.*` or a regex), multi-select, and chained dependencies (one variable populates another).

Question 13

How do you create an alert in Grafana?

Accepted Answer

In Grafana 11, alerting is centralized — Alerting → Alert rules. You define a rule with: (1) a query against a data source, (2) a threshold condition (`is above 0.05`), (3) an evaluation interval (every 30s), and (4) a duration the condition must hold ('Pending → Firing' after 5m). Firing rules emit alerts that match label-based routes to contact points (Slack, PagerDuty, email, webhook). The biggest shift from the legacy panel-based alerting (pre-v8) is that alerts now live independently of panels — you can have an alert without a dashboard, and one alert can use multiple queries from different data sources. Always set a 'For' duration; without it, a brief blip will page you. The standard SRE rule of thumb: For = at least 5 minutes for non-critical, 1-2 minutes for critical SLO burns.

Question 14

What is the Explore view in Grafana?

Accepted Answer

Explore is the ad-hoc query view — no dashboard, no panel, just a query editor and a result. It's where on-call engineers live during incidents. Pick a data source, write a query, see the result with a time picker that's easy to slide. Explore supports split view (two queries side by side, often Prometheus + Loki to correlate metrics with logs) and one-click jumps from logs to traces (via Tempo) using exemplars or trace IDs. The Logs panel in Explore has a histogram on top showing log volume over time, which is invaluable for spotting incident windows. Pro tip: when something looks weird in a dashboard, click the panel title → Explore — it opens the panel's query in Explore where you can mutate it freely without breaking the dashboard.

Question 15

How do you import a dashboard in Grafana?

Accepted Answer

Three ways: (1) UI — Dashboards → New → Import, paste JSON or upload a file or paste a Grafana.com dashboard ID (e.g. 1860 for the famous Node Exporter Full dashboard). (2) HTTP API — `POST /api/dashboards/db` with the JSON. (3) File-based provisioning — drop a JSON file in `/etc/grafana/provisioning/dashboards/` with a YAML config pointing at the directory. The third option is the production answer — dashboards live in git, get reviewed in PRs, and Grafana auto-loads them on restart. Common gotcha: data source UIDs are baked into the dashboard JSON. When you import across environments (staging → prod), either replace the UID or use `__inputs` placeholders that the import dialog substitutes.

Grafana Interview Questions

What is Grafana and what problems does it solve?

What is a dashboard and what is a panel in Grafana?

What is a data source in Grafana?

What is PromQL and how do you write a basic query?

What is LogQL and how is it different from PromQL?

What is MetricsQL and when does it come up?

What are dashboard variables and why are they useful?

How do you create an alert in Grafana?

What is the Explore view in Grafana?

How do you import a dashboard in Grafana?

What's the difference between transformations and queries?

How do you manage users and access in Grafana?

How do you set up high-availability Grafana?

How does Grafana's unified alerting v2 work?

What are contact points, silences, and mute timings?

How do you optimize a slow dashboard in Grafana?

What is the Scenes API and what changed in Grafana 11?

How do you correlate metrics, logs, and traces in Grafana?

How do you provision Grafana for production (dashboards, data sources, alerts)?

How do you handle on-call rotations with Grafana OnCall?

What is a 'recording rule' and when should you use one?

How do you write a custom Grafana plugin?

How does Grafana handle dashboard versioning and exporting?

What are exemplars and how do they help with debugging?

How do you set up a multi-tenant Grafana instance?

How would you design an observability platform for a company with 500+ microservices?

How do you implement effective SLO-based alerting in Grafana?

How do you build a blameless postmortem culture using Grafana?

How do you debug a Grafana instance that has high CPU/memory usage?

How would you migrate from a legacy monitoring stack (Nagios, Datadog) to Grafana + LGTM?

Companies Hiring Grafana

Salary Insights

Frequently Asked Questions

Is Grafana the same thing as Prometheus?

How much does a Grafana / SRE / Observability engineer earn in India?

What's the difference between Grafana, Grafana Cloud, and Grafana Enterprise?

Should I learn PromQL, LogQL, or both?

Is Grafana hard to learn coming from Datadog or New Relic?

Introduction