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Pagerduty Software Engineer Interview Guide

Pagerduty Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

A Software Engineer at Pagerduty is responsible for building and scaling the digital operations management platform that thousands of global enterprises rely on to keep their critical systems online. When digital services fail, Pagerduty is the central nervous system that orchestrates the response. Consequently, the software you write here directly impacts system reliability and incident response times for major platforms worldwide. Engineers at Pagerduty tackle complex, high-throughput distributed systems challenges, working on real-time event routing, advanced scheduling algorithms, and high-availability infrastructure. Whether you join the Core Product team, the Authorization Team, or the HR Infrastructure & Operations group, your work will focus on resilience, low-latency execution, and seamless user experiences.

This guide is scoped to a Software Engineer candidate at Pagerduty.

Focus areas

  • Algorithms & Data Structures
  • Building an MVP / Starter App
  • Technical Communication / Explaining Thought Process

The Pagerduty interview process

Pagerduty candidates report 5 rounds over 4-6 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screen

Initial discussion to align on your background, salary expectations, and interest in the company.

What to demonstrate

  • Initial discussion to align on your background, salary expectations, and interest in the company
  • Depth in Algorithms & Data Structures

How to prepare

  • Be able to walk your CV end to end in two minutes, and say why this company specifically.
  • Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.

Hiring Manager Call

Call focusing on your career history, technical achievements, and behavioral scenarios.

What to demonstrate

  • Call focusing on your career history, technical achievements, and behavioral scenarios
  • Depth in Algorithms & Data Structures

How to prepare

  • Prepare two projects you led end to end, each with the decision you owned and what it cost.
  • Have three questions about the team's roadmap and how success is measured in the first six months.

Take-Home Coding Assignment

Build a small, functional application (MVP) in the language of your choice.

What to demonstrate

  • Build a small, functional application (MVP) in the language of your choice
  • Depth in Algorithms & Data Structures

How to prepare

  • Answer aloud and timed: Expand a pre-built skeleton application to integrate with an external API, demonstrating how you handle network failures and asynchronous data parsing.
  • Answer aloud and timed: Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notifications with strict rate-limiting.

Live Collaborative Session

Pair with an engineer to expand upon your take-home code.

What to demonstrate

  • Pair with an engineer to expand upon your take-home code
  • Depth in Algorithms & Data Structures

How to prepare

  • Answer aloud and timed: Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and foreign keys.
  • Answer aloud and timed: Architect an API gateway that handles high-throughput traffic, detailing how you would manage authentication, caching, and failover.

Onsite/Virtual Loop

Comprehensive evaluation of system design, data modeling, and behavioral fit.

What to demonstrate

  • Comprehensive evaluation of system design, data modeling, and behavioral fit
  • Depth in Algorithms & Data Structures

How to prepare

  • Answer aloud and timed: Design a high-volume data pipeline that ingests system metrics, aggregates them in real time, and stores them for historical analysis.
  • Answer aloud and timed: Explain how you would migrate a monolithic user service to a microservices architecture without causing downtime for active users.

Where candidates lose points

Treat the Take-Home Seriously

The take-home MVP is not just a screening filter; it forms the entire foundation of your subsequent live coding round. Write clean, well-structured, and thoroughly commented code. Ensure you have robust error handling and basic test coverage in place.

Do not rush through the take-home MVP assignment

If your base code is messy or lacks structure, you will find it incredibly difficult to add the requested live features during the high-pressure, 60-minute collaborative coding interview.

Think Out Loud

During both the pair-programming and system design rounds, your interviewers are evaluating your thought process and communication style. Explain your assumptions, voice any trade-offs you are considering, and clarify requirements before writing code or drawing diagrams.

Questions & practice

Write a program that reads a dataset of key-value pairs and find specific combinations that sum to a target va

Medium · Application Development & Live Refactori

Write a program that reads a dataset of key-value pairs and find specific combinations that sum to a target value, ensuring optimal time and space complexity.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.

Follow-up

  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Identify the heaviest tenants in a five-minute window under memory pressure

Medium · top-k · heavy hitters · streaming

The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.

Approach

  1. Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
  2. Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
  3. State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
  4. Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.

Follow-up

  • The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
  • Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?

Archive a resource graph without breaking live references or recursing

Medium · graph traversal · topological order · tenant isolation

Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.

Approach

  1. Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
  2. Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
  3. Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
  4. Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.

Follow-up

  • The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
  • The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?

Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and

Medium · System Design & Data Modeling

Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and foreign keys.

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. Handle the rows that do not match: that is usually the actual question.

Follow-up

  • How does the query change if that join becomes one-to-many?
  • What happens to this when the table is ten times larger?

Write a SQL query utilizing complex joins and aggregations to count active incident records across multiple ta

Medium · Systems Troubleshooting & Operations

Write a SQL query utilizing complex joins and aggregations to count active incident records across multiple tables based on specific regional criteria.

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. Handle the rows that do not match: that is usually the actual question.

Follow-up

  • How does the query change if that join becomes one-to-many?
  • What happens to this when the table is ten times larger?

Build a minimal viable product (MVP) for a cookbook/recipe application, then add live features to filter recip

Medium · Application Development & Live Refactori

Build a minimal viable product (MVP) for a cookbook/recipe application, then add live features to filter recipes by ingredients or calculate total preparation time.

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Implement a basic task management (todo) application, and subsequently refactor it to support prioritized queu

Medium · Application Development & Live Refactori

Implement a basic task management (todo) application, and subsequently refactor it to support prioritized queues and nested sub-tasks.

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Create a configuration parser that validates nested brackets or parentheses, ensuring the input is structurall

Medium · Application Development & Live Refactori

Create a configuration parser that validates nested brackets or parentheses, ensuring the input is structurally sound.

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Expand a pre-built skeleton application to integrate with an external API, demonstrating how you handle networ

Medium · Application Development & Live Refactori

Expand a pre-built skeleton application to integrate with an external API, demonstrating how you handle network failures and asynchronous data parsing.

Approach

  1. Say who the caller is and what they do when the call fails halfway.
  2. Define the identity of a request so a retry cannot double-apply it.
  3. Separate accepted, pending, failed and confirmed; they are different facts.
  4. Design the error taxonomy before the success shape; callers branch on it.

Follow-up

  • What happens if the caller retries after a timeout?
  • How does a client discover it is on an old version of this contract?

Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notificatio

Medium · System Design & Data Modeling

Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notifications with strict rate-limiting.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Architect an API gateway that handles high-throughput traffic, detailing how you would manage authentication,

Medium · System Design & Data Modeling

Architect an API gateway that handles high-throughput traffic, detailing how you would manage authentication, caching, and failover.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Design a high-volume data pipeline that ingests system metrics, aggregates them in real time, and stores them

Medium · System Design & Data Modeling

Design a high-volume data pipeline that ingests system metrics, aggregates them in real time, and stores them for historical analysis.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Explain how you would migrate a monolithic user service to a microservices architecture without causing downti

Medium · System Design & Data Modeling

Explain how you would migrate a monolithic user service to a microservices architecture without causing downtime for active users.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

You are logged into a remote Linux server that is experiencing high latency. Walk through the command-line too

Medium · Systems Troubleshooting & Operations

You are logged into a remote Linux server that is experiencing high latency. Walk through the command-line tools and steps you would use to identify the bottleneck.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Configure and start a caching daemon (such as Memcached) from the command line, and explain how you would veri

Medium · Systems Troubleshooting & Operations

Configure and start a caching daemon (such as Memcached) from the command line, and explain how you would verify its operational statistics.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Walk through how you would diagnose a database connection pool exhaustion issue in a production environment.

Medium · Systems Troubleshooting & Operations

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Explain the trade-offs between relational databases and NoSQL databases when storing high-frequency event logs

Medium · Systems Troubleshooting & Operations

Explain the trade-offs between relational databases and NoSQL databases when storing high-frequency event logs.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Suggested practice checklist

Built from the rounds and topics Pagerduty candidates report.

Day 1 — Map the Pagerduty loop

  • Write out the reported sequence: Recruiter Screen, Hiring Manager Call, Take-Home Coding Assignment, Live Collaborative Session, Onsite/Virtual Loop.
  • For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 5 reported rounds, with the weakest marked.

Day 2 — Work Algorithms & Data Structures

  • Spend the session on Algorithms & Data Structures, which Pagerduty candidates report being tested on.
  • Write one worked example in Algorithms & Data Structures and time yourself on it.

Deliverable: One timed worked example in Algorithms & Data Structures.

Day 3 — Work Building an MVP / Starter App

  • Spend the session on Building an MVP / Starter App, which Pagerduty candidates report being tested on.
  • Write one worked example in Building an MVP / Starter App and time yourself on it.

Deliverable: One timed worked example in Building an MVP / Starter App.

Day 4 — Work Technical Communication / Explaining Thought Process

  • Spend the session on Technical Communication / Explaining Thought Process, which Pagerduty candidates report being tested on.
  • Write one worked example in Technical Communication / Explaining Thought Process and time yourself on it.

Deliverable: One timed worked example in Technical Communication / Explaining Thought Process.

Day 5 — Answer out loud: Application Development & Live Refactoring

  • Answer aloud, timed: Build a minimal viable product (MVP) for a cookbook/recipe application, then add live features to filter recipes by ingredients or calculate total preparation time.
  • Answer aloud, timed: Implement a basic task management (todo) application, and subsequently refactor it to support prioritized queues and nested sub-tasks.

Deliverable: Spoken answers to 2 reported Application Development & Live Refactoring question(s), under time.

Day 6 — Answer out loud: System Design & Data Modeling

  • Answer aloud, timed: Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notifications with strict rate-limiting.
  • Answer aloud, timed: Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and foreign keys.

Deliverable: Spoken answers to 2 reported System Design & Data Modeling question(s), under time.

Day 7 — Answer out loud: Systems Troubleshooting & Operations

  • Answer aloud, timed: You are logged into a remote Linux server that is experiencing high latency. Walk through the command-line tools and steps you would use to identify the bottleneck.
  • Answer aloud, timed: Write a SQL query utilizing complex joins and aggregations to count active incident records across multiple tables based on specific regional criteria.

Deliverable: Spoken answers to 2 reported Systems Troubleshooting & Operations question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

Describe a time when you made a significant technical mistake in a production system. How did you identify it,

Medium · Behavioral & Leadership

Describe a time when you made a significant technical mistake in a production system. How did you identify it, resolve it, and what did you learn?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Tell me about the largest or most complex engineering team you have worked on. How did you manage communicatio

Medium · Behavioral & Leadership

Tell me about the largest or most complex engineering team you have worked on. How did you manage communication and technical alignment?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Describe a situation where you had a strong technical disagreement with a peer or manager. How did you resolve

Medium · Behavioral & Leadership

Describe a situation where you had a strong technical disagreement with a peer or manager. How did you resolve it to keep the project moving forward?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Who was the best mentor you ever had, and what specific qualities made them effective?

Medium · Behavioral & Leadership

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Why do you want to work at Pagerduty, and how do you approach maintaining system reliability during your own o

Medium · Behavioral & Leadership

Why do you want to work at Pagerduty, and how do you approach maintaining system reliability during your own on-call shifts?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?