Once your application is up and running in the hands of users, the real work of quality and reliability begins. Post-launch support isn’t a cost center; it’s a crucial competitive edge that determines whether users stick with you or switch to a competitor. India has become the world’s best location to provide post-launch support and maintenance for applications with well-trained engineers and low costs, 60-70% less than that of the US or European markets, making it a perfect choice for startups as well as for enterprises.
This In Depth covers all aspects of building post-launch support from India: the three-tier support model, how to build out your team to support your solution, estimating realistic costs, tracking performance with MTTR metrics, developing incident playbooks for common incidents, managing 24/7 on-call rotations, and sustainable upgrading cadence for your application.
Contemporary support operations divide the technical personnel into tiers of specialization according to the complexity of problems and the necessary expertise. This time-tested model enables routine issues to be positively addressed at a low cost and promptly at first contact, while more complex technical challenges are escalated to subject matter experts.
Level 1 support is the first engagement with users experiencing problems with your application. These are the “front-line” staff who handle most of the ballpark questions that don’t require drilling down into the tech. L1 support for password reset, basic troubleshooting for login problems, help with key functions, checking on account status, simple payment concerns, and submitting support tickets with user information. Level one support for password resets, basic troubleshooting for login problems, assistance with core applications, checking account status, simple queries regarding payments, and submitting support tickets containing user details.
L1 agents make up 60-70% of the total support tickets because most users have common questions or issues that can be tackled with the existing functionality of the application. The best L1 agent needs to possess excellent communication skills, a basic understanding of the product, patience, and the capability to execute troubleshooting instructions.
Salary Information for L1 Support Agents in India L1 support agents make anywhere between ₹18,000 to ₹35,000 a month in India, depending on their experience. Entry-level agents (0-1 years) receive ₹20,000-25,000 per month, and senior L1 supervisors with 3-5 years of experience earn ₹35,000-45,000 per month.
There is a critical metric that the L1 uses, and that is the first contact resolution rate, or how many issues they resolved without escalating them. The best L1 support teams have a first contact resolution rate of 60% – 75%, greatly reducing the cost impact of support because every escalated incident consumes resources from higher-cost L2 and L3 engineers.
L1 agents have to escalate the tickets to L2 support when they face problems that are out of the scope for them – something that needs system-based troubleshooting or code review. Level 2 engineers are technical professionals who troubleshoot complex issues, analyze system logs, change configurations, and sometimes write code patches.
L2 engineers also handle such issues as database connection failures, API integration errors, server configuration mistakes, authentication system outages, payment gateway integration problems, and performance bottleneck analysis. They need to be able to understand your application’s layout, read server logs, interact with databases, understand APIs, and just have solid troubleshooting skills.
It is estimated that 20% to 30% of total support volume is handled by L2 support; however, due to each ticket taking much longer (2-8 hours on average), you have much fewer L2 agents than L1. Approximately 1 L2 engineer for every 10-15 L1 agents is a common ratio of L2 to L1.
In India also L2 support engineers fetch better remuneration as they are more experienced. Junior L2 engineers (1-3 years of experience) earn ₹45,000 to ₹65,000 per month. Mid Level L2 Engineer (3 -5 years) – ₹65,000 to ₹85,000 per month. Senior L2 specialist gets 85000 to 110000 per month.
Level 3 is your most senior technical staff – expert engineers and system architects who address issues that L2 teams aren’t able to resolve. These are usually less than 5 percent of all tickets, but have the highest impact on the business.
L3 engineers work on critical database incidents that impact all users, high-severity security issues that are found in production, notably performance problems that require architectural changes, multi-system integration problems, and infra-level outages. They are highly experienced professionals, mostly bringing in 5-10+ years of experience and are certified in cloud platforms (AWS, Google Cloud, Azure), advanced database systems, or specialized technologies.
In India, L3 support engineers’ salary is between 100,000 to 150,000+ INR per month, and senior architects between 180,000 to 250,000 per month. Most organizations have about 1-3 L3 engineers on standard applications, and these people are splitting their time between reactive support and proactive enhancement work.
India’s Monthly App Maintenance Cost by Complexity Level
Organizational Structure for Support Teams
In addition to the three support tiers, there are a number of other important roles that help deliver effective post-launch support.
There needs to be someone who coordinates the support team, monitors performance metrics, coordinates schedules and on-call rotations, and interfaces with other departments for major concerns. In India, the salary of a support team lead or manager generally ranges between ₹60,000 and ₹100,000 per month, depending on the size of the team and the experience. They are responsible for SLA compliance, coaching agents, managing escalations beyond technical resolution, and monitoring for trends that suggest product issues that need immediate attention.
During a severe impact on a large audience, an incident commander is always needed. This person acts as a bridge between the L2 and L3 groups, provides communication to product managers and executives around impact and timeframes, manages communication to customers, and drives post-incident documentation. The incident commander isn’t necessarily the person who fixes the issue — they coordinate the work of the people who are.
A quality support company will produce documentation so people don’t have to ask the same questions repeatedly. An owner is a knowledge base maintainer and writer, troubleshooting guides, solutions to frequently asked questions, and updating documentation as the product evolves, generally expects ₹20,000 to ₹40,000 per month, depending on expertise and writing skills.
As your support team scales, having a support interaction audited/quality scored/SLA compliance checked, along with coaching opportunities identified and standards upheld, becomes a valuable role. This position is priced around ₹35,000 to ₹60,000 per month and can bring down the number of support-related customer complaints immensely.
India’s Support Engineer Pay by Experience and Support Level
Knowing the true costs enables you to accurately budget and decide whether to outsource or build an in-house team.
Personnel usually account for 70-80 percent of a support agency’s total budget. That’s not just base pay, but also benefits, taxes, and overhead. In India, while calculating for PF contributions (about 12 percent of salary), gratuity provisions, leaves, and HR admin overheads, one can add around 35-45 percent to the base salary for a worker, cost fully-loaded.
For instance, an L1 agent with a salary of ₹25,000 per month actually costs about ₹33,750 per month when you account for overhead and benefits. A level 2 engineer with a base salary of ₹75,000 becomes an approximate cost of ₹105,000 per month with benefits.
You own the right tools to run your support operations effectively. These may be your ticketing systems (Jira Service Management, ServiceNow, etc.), knowledge base platforms (Document360, Confluence, Zendesk, etc.), communication tools (Slack, Microsoft Teams, etc.), incident management tools (PagerDuty, Squadcast, etc.), your monitoring stacks (New Relic, DataDog, your own custom solutions, etc.), and your phone systems or VoIP to speak with your customers. Total technology expenses are generally between ₹15,000 and ₹50,000 per month, based on the choice of tools and size of team.
If your support team is office-based (as is typical in India), you have overhead costs for office space, internet, computers, and supplies. In leading Indian IT cities like Bangalore, Pune, or Mumbai, the cost of office space varies from 250 to 500 rupees per square foot per annum. A squad of 15 support agents can be housed in 600-800 square feet, for a cool space fee alone of ₹3,000 to ₹5,000 per month. For distributed teams or remote workers, these costs are significantly lower.
A technical product support needs continuous education since the product changes. New team members require onboarding (usually ₹5,000 to ₹15,000 per head), and current team members require refresher training on product updates, new features, and upgraded support methods. You can spend about ₹20,000 to ₹50,000 a month on training for your team.
For a simple application (low complexity, simple features, little to no backend infrastructure), monthly support costs would be:
For a mid-level complexity application (typical SaaS or e-commerce app with multiple features and moderate technical depth):
For a complex application (enterprise systems, high-traffic, multiple integrations, strict compliance requirements):
These rates are according to the market in India for the year 2024-2025. Outsourced support is generally priced at a range of $7 to $16 an hour per agent, depending on the complexity and location within India, versus $40-65 an hour in Western nations such as Australia.
Encourage Team Growth and Cost Increase with Ticket Volume
An SLA is basically a commitment that customers make, knowing how fast they can get support. Various matters call for different turnaround times, so companies often are a little more granular with their definition of SLAs, having different tiers identified by issue severity.
Severe (Severity 1 / Priority 1): The system is either completely unavailable, or essential functionality is so degraded that the user base (all users or a significant portion) can be considered impacted. For payment apps, not a single payment can be accepted. Users can’t browse or buy on e-commerce sites. You’re promising a 15-30 minute response and a 4-hour fix for these incidents.
High (Severity 2 / Priority 2): The application is partially operational or a major function is inaccessible, but a workaround is available. For example, most functionality is available to users, but payment processing is slow, or specific user categories are unable to log in. Response time SLA is normally 1 hour, and the resolution time varies from 4-8 hours.
Medium (Severity 3 / Priority 3): A functionality is either not working properly, but users can still do what they want by other means, or the performance is reduced, but it is still acceptable. These could be certain reporting tools with inaccurate sales numbers, or non-critical processes that are unusually slow. Resolution of Response time SLA is 4 hours, and the target for resolving is 24 hours.
Low (Severity 4 / Priority 4): Cosmetic problems, suggestions, or minor defects that don’t prevent users from achieving their goals. Response time SLA is 8 – 24 hours, and there is no rigid resolution time target.
First Response Time (FRT): How fast does your team respond to the support request? You should respond as soon as you can to the email, even if you can’t fix the problem straight away. Best practice across industries for critical issues is a response time of 15 minutes during business hours and 30 minutes for after-hours critical incidents.
Mean Time to Resolution (MTTR): The average time between an incident being raised and resolved. MTTR equation: sum of resolution time intervals/number of issues resolved. For simple issues, this could mean an MTTR of 30 minutes to 2 hours. MTTR for complex incidents may range from 8 to 24 hours. Monitoring MTTR can reveal bottlenecks—if your L2 engineers are regularly taking 12+ hours to close issues, that may be a sign you need more L2 staff, or better troubleshooting tools.
First Contact Resolution Rate: The proportion of issues resolved by L1 support without escalation. Increasing this percentage from 50% to 70% will have a significant positive impact on both support costs and customer satisfaction.
SLA Compliance Rate (%): Percentage of tickets that have met their Vi and Vd time durations for response and resolution. This metric can also be used to determine if the team size is adequate. “95+ percent SLA compliance is a sign that we have good capacity.” “70 percent compliance means they need more staff.”
Ticket Volume and Trending: Number of support tickets received daily/weekly/monthly, and whether or not the volume is increasing or decreasing. Higher tickets could be a product issue or represent more users.
SLA Response and Resolution Times by Severity of Incident
Although MTTR tells you how quickly issues are fixed, MTBF tells you how long your system runs without breaking. MTBF = average total operating time / number of failures. For instance, if a software system ran for 1000 hours and had 10 failures, MTBF would be 100 hours.
MTBF is useful in providing companies with the ability to evaluate the reliability of a system, maintenance planning, and product design. High values in MTBF imply the system is reliable, with fewer failures, so the performance is expected to be smooth and predictable. Most good apps are aiming for an MTBF of at least 500-1000+ hours between critical events.
An incident playbook defines your team’s processes for managing critical incidents in much the same way emergency procedures are defined for physical emergencies, where people and responses are predetermined to avoid missing any step during a high-stress event.
Your incident playbook should define a critical incident (generally S1 issues), provide a decision tree for determining severity of an incident, escalation procedures with details on who should be called and in what order, communication templates for both internal and external notifications, detailed investigation instructions for the top common critical issues, a well-defined incident command structure, documentation requirements for the post incident analysis, and a schedule for updates to stakeholders.
Incident Commander: Leads, orchestrates the response, monitors actions, and reports status to leadership. This is usually an L3 engineer, tech lead, or support manager.
Technical Lead/Primary Responder: The person is hands-on at diagnosing and remediating the incident. This might be an L2 engineer digging through logs or an L3 engineer on a system-level fix.
Communication Lead: Handles customer communication, drafts status updates, and liaises with marketing/sales in the event the incident is customer-visible. This stops conflicting information to customers.
Secondary/Backup Responders: May support the primary responder, perform allied functions, or substitute for the primary responder if he/she becomes stuck or fatigued.
Database Connection Failure: Indicators are all users experiencing 500 errors, applications timing out, or not being able to load any pages. Response: L2 pings database server, confirms connectivity from the app servers, checks for recent database changes, checks for disk space, checks connection pool settings, restarts services, or escalates to DBA (L3).
API External Service Integration Failure: An external payment gateway, analytics platform, or third-party API is down or giving errors. Response: L2 reviews the service status page of the external service, confirms network connectivity to their servers, reviews recent changes to API credentials, checks rate limits, and either implements fallback behavior or escalates to the external provider.
Memory Leak or Resource Exhaustion: Application servers are slow to consume more and more memory until they crash. Response: L2 reviews current memory usage, looks at recent code changes, finds out which process is leaking memory, sets up a temporary restart schedule, while L3 works on a permanent fix.
Security Incident: Unauthorized access has been detected. You have been informed that your system may be the source of data compromise, or an excellent security hole has been made public. Response: Isolate affected systems, preserve logs for forensic analysis, notify the security team and leadership immediately, review access logs for the extent of compromise, apply mitigations, and start incident post-mortem.
Workflow for Support Escalation: From L1 to L3 Support Resolution
Key Metrics for the Support Operations Dashboard
Most applications require support outside of the normal business day. 2 AM critical issues must be addressed within 30 minutes, not wait until Monday morning. Good on-call rotations mean there is always someone available and that your team doesn’t get burnt out.
After-Hours Only Model: L1 and L2 staff members are staffed during standard business hours (9 AM to 6 PM). For after-hours, evenings, weekends, and holidays, one person (primary) and one backup are on call. This individual gets notifications by phone if there’s a problem. For low-traffic apps, this is usually the cheapest, but you might miss problems if the on-call is unresponsive. You have to have at least 3-4 people rotating through this schedule.
Daily Rotation Model: Two L1/L2 agents work traditional shifts while the on-call responsibility switches over daily. The new person (switching in at 11 AM or other prearranged time) assumes the on-call position for 24 hours. This approach is a good choice for medium-traffic applications and guarantees that new people will always be on call. You need 4-5 people in the rotation.
Weekly Rotation Model: One person is on call for the entire week (Monday through Sunday, 24/7). On the following Monday, it’s the other person’s turn. This arrangement works well for mature, relatively stable applications that don’t generate large numbers of incidents. You only need 3-4 people in the rota, but the burnout risk is higher if incidents are frequent in someone’s week.
Regional Rotation Model: Your team, located in India, is on-call during India business hours (which are approximately the US overnight and early morning). Your US team (assuming you have one) is on call during its business hours. That way, nobody is forced to be on call during their sleeping hours regularly. This model works well for globally distributed organizations, but it demands having support personnel situated in different time zones.
Distribute Evenly: Rotate on-call evenly amongst all members of the team. Monitor the holding period, who was on call when, and ensure that no one carries that burden unbalanced.
Specify Escalation Policies: If the primary oncall does not respond within 5 minutes, so long as the subsequent timer has not expired, page the secondary. Wait another 5 minutes: If this late 5-minute period after the initial 5 is still without response, page the tertiary on-call person. This stops escalations from falling through the cracks.
Offer Compensation: Serving as the on-call doctor is stressful and life-altering. Pay people, give them extra days off, or benefits of some other kind.
Establish Response Expectations: The on-call person should be responding to alerts within 5-15 minutes (depending on the alert severity). They don’t have to worry about fully resolving the problem immediately—they just have to acknowledge the problem, determine the severity, and start investigating.
Leverage Tools: Invest in on-call management software (PagerDuty, Squadcast, Spike) that not only escalates alerts automatically, but routes them thoughtfully based on availability, expertise, and more.
On-Call Rotation Models for Round-the-Clock Assistance
Your service team also needs to be armed with tools to do their job well.
Ticketing System: Is Jira Service Management or Zendesk your main ticket management platform? All the customer interactions are logged here, enabling you to monitor the progress, assign them to the right person, and make sure nothing is missed.
Knowledge Base: Solve common problems, how-tos, and FAQs with knowledge-based documentation. Systems such as Confluence, Document 360, or Zendesk Knowledge Base are excellent choices.
Monitoring and Alerting: Datadog, New Relic, or Prometheus will notify your staff of problems—hopefully before anyone calls them.
Communication Platform: Use Slack or Microsoft Teams to communicate internally with your team while an incident is in progress.
Incident Management: PagerDuty or Squadcast for managing your on-call scheduling, alert routing, and incident orchestration.
Chat Support: Additional apps (such as Intecom, Drift, or Zendesk Chat) for chatting with customers in real time.
Collaboration: Confluence, or similar, for sharing documents internally, runbooks, and team knowledge.
The support crew is not merely reactive to problems—they also take care of preventative maintenance, updates, and enhancements for your application.
Monthly Patches: It’s not uncommon to release patches on the first Tuesday of the month. These releases may contain bug fixes, performance enhancements, security updates, and/or minor feature changes. Plan on 2 to 3 hours of additional support load, as users do report problems post major updates.
Quarterly Feature Releases: Most organizations strive to ship sizeable new features a few times a year (every 3 months/quarter/quarter-of-a-year). These are generally much more dangerous than patch releases and require additional monitoring and resources of support staff.
Security Updates: These occur on a “when needed” basis when a security risk is found. Critical security updates for any software vendor may be released on any day of the week if there is a sufficiently critical vulnerability.
Operating System Compatibility Updates: When Apple introduces a new iOS version, or Google introduces a new Android version, your app needs to be tested (and updated). These generally occur 2-4 times annually, so trade/property 1-4.
Documentation and Knowledge Base Updates: Update your Knowledge Base as features change or new features are released. Don’t let your documentation get behind your product.
Typical Timeline for App Upgrades and Releases
In advance of any release, your support team needs to be ready. Weeks in advance: skim through the documentation of changes and make guides for support. Days before: drill on incident responses to known risky changes. Hours before: make sure the on-call team knows what’s changing. Post-release: Provide intensive monitoring of the support ticket queue and application performance for 4-8 hours.
Track these metrics to evaluate your support operation’s health:
MTTR (mean time to resolution): The average time from ticket opening to ticket closure. Target 2-4 hours for easy cases. Target 8-24 hours for complicated problems.
MTBF (Mean Time Between Failures): For applications, this is how long the system is up before it crashes. Higher is better. Target 500-1,000+ hours between critical incident reporting.
First Contact Resolution Rate: The proportion of tickets resolved by L1 without escalation. Target 60-75 percent.
SLA Compliance: The percentage of tickets that meet their response and resolution deadline SLAs. Target 95+ per cent.
Customer Satisfaction Score: Ask users to rate their support experience. Target: 8 +/10.
Cost to support per user: Total monthly support cost / monthly active users. Benchmark against your revenue per user.
Ticket Volume Trends: Monitor tickets per 1000 users to distinguish growth-based volume from quality-driven volume.
Both are the right questions to ask. Outsourcing to a support firm offers flexibility—you pay for only what you consume, you don’t hire/fire, and the vendor manages. Generally, offshore support costs between ₹12 and ₹25 per hour, depending on difficulty level, or $7 to $16 per hour for providers located in India.
While building an internal team means better control, simpler scalability, and better product understanding with time, it also takes more work to manage.
For early-stage startups with less than 1,000 daily active users, outsourcing often makes sense. For mature applications used by thousands of people every day, in-house teams tend to turn out to be more cost-effective. BSR outsourcing Level 1 / Level 2 and in-house L3 – the hybrid approach offers a good balance and is often where that optimal cost benefit trade-off lies.
Post-launch support from India is an attractive proposition to strike the right balance for cost vs quality customer support. With the help of a well-defined three-tier support structure, realistic SLAs, detailed incident playbooks, best-fit technology tools, and effective on-call rotations management, you can develop a support process that ensures that your application runs smoothly, while your team enjoys a balanced work-life stability.
Success comes down to treating support as a strategic investment, not a cost center. Apps with strong support operations enjoy higher retention, better reviews, more word-of-mouth referrals, and ultimately better business outcomes. The expertise of India’s support professionals, proven methodologies, and the right tools give your organization the edge in delivering the support experience that leads to long-term success for your app.
