Posted on

What is API Observability

API Observability is a key component to properly execute APIOps Cycles and ensure your building something of value for your API users. If you’re not familiar with APIOps Cycles, take a look at this guide which provides an agile framework to quickly build APIs that are business-oriented and serve customer needs. API Observability itself is an evolution of traditional monitoring and born out of control systems theory.

Traditional monitoring focuses on tracking known unknowns. This means you already know what to measure like Request Per Second or Errors Per Second. While the metric value may be unknown beforehand, you already know what to measure or probe such as a counter to track requests into buckets. This makes it possible to report on the health of a system (like Red, Yellow, Green), but is a bad tool for troubleshooting engineering or business issues which usually require asking arbitrary questions.

Posted on

The Highest Ranked Business Intelligence Software in 2020

These tools are used by data science professionals and businesses to collect, evaluate, monitor, and predict future business results through basic observations of the company's data. Trends are becoming the standard for business practices, strategic designs, and increasingly critical methods of growing profit through the use of successful visualizations and the provision of real-time online insights. Here are the Top 10 Business Intelligence Software in 2020.

Shortlist 2020: The Best BI Tools In The Market (TIBCO Spotfire | Qlik Sense | SAP Crystal | Bizdata Bizintel360 | Tableau Desktop | TIBCO Jaspersoft | SAP Analytics Cloud | SAP Lumira Discovery | Birst | Microsoft Power BI | QlikView)

Posted on

How to Properly Deprecate APIs

As with any product lifecycle, a key responsibility for API architects and API product owners is deciding when to sunset or retire a feature or offering. The API lifecycle is no different, but requires careful planning to carry out the deprecation to minimize customer impact. Unlike a packaged solution or module which is more of a black box, APIs enable your customers to build custom functionality which may have requires months of integration work and testing. Without the correct assessment or process, you could prematurely deprecate a critical service causing a storm of support tickets.

This guide walks through the best practices of deprecating an endpoint and shows, by example, how to do it with an analytics platform.

Posted on

Why Data-Driven Customer Success is Essential in Today’s COVID World

In today’s unprecedented economic downturn, it’s more difficult than ever to find and close new customers. The onus is now on maintaining existing customers as productive users of your product. By closely monitoring API metrics, Customer Success Management (CSM) teams can get an early warning on those that are at risk of churning, and rectify things before it’s too late.

Customer Acquisition Versus Customer Retention: At Least 5X Difference in Cost

According to different surveys, the average cost of acquiring a new customer is between 5X and 25X the cost of retaining an existing one. That was in the pre-COVID era. In today’s world, it’s probably more.

Posted on

What is Developer Relations and What are Common Roles?

Developer Relations is not simply a role or department at API-first companies. Developer relations is a mindset of getting developers adopt a platform and making them successful with their initiatives rather than attempting to sell to those developers. This makes developer relations different from traditional sales and marketing roles. However, if you ask “What is Developer Relations?”, you may get many ambiguous responses as developer relations is a catch all phrase for a variety of different roles and titles. Some titles include “Developer Advocate” and Developer Evangelist”, but can also include other newer titles like “Developer Experience Manager.”These roles vary company to company and even across teams within a company.

This post outlines some of the different roles within devrel, such as:

Posted on

What Does API Monitoring Mean for API Product Managers and Growth Teams

Today, countless engineering teams have leveraged API monitoring to track infrastructure health and report when services are down or unhealthy. There are a variety of API metrics that can be tracked that are aligned with engineering goals, such as uptime, average latency, requests per minute, and errors per minute. 

However, these metrics are not aligned with the business goals of product owners and growth teams. This article goes through how to leverage API monitoring tools to further your business growth and product road map.

Posted on

How to Market Your SaaS Platform to Developers During a Recession

With the recent downturn on public stock markets due to COVID-19, a recession or depression is almost inevitable. We likely see mass failures across retail, travel, entertainment, and other industry sectors. The spillover from coronavirus disease and the following shelter-in-place can have drastic consequences in the startup world. 

Small brick and mortar businesses that were shuttered due to shelter-in-place rules will no longer spend money on Facebook or Yelp to promote their business nor will they maintain their SaaS subscriptions. Large enterprises will pull back spending in sales and marketing in anticipation of a recession. This could cause a reduction in seat counts or usage for the SaaS contract. Similarly, sales teams may find CFOs and financial controllers are blocking many more purchases than before forcing deals to be stuck in procurement or legal review.

Posted on

REST API Design Best Practices for Parameters and Query String Usage

When we’re designing APIs, the goal is to give our users some amount of power over the service we provide. While HTTP verbs and resource URLs allow for some basic interaction, oftentimes, it’s necessary to provide additional functionality or else the system becomes too cumbersome to work with.

An example of this is pagination: we can’t send every article to a client in one response if we have millions in our database.

Posted on

Best Practices for Developer Relations Programs to Measure Success of an API Platform

Each developer relations program has a different opinion on what should be north star metrics to measure the success of their platform. Some metrics are valid while others can be what are called vanity metrics. This post discusses which metrics you should or should not be tracking.

What to Measure

The goal of developer relations is to ensure third-party developers are able to leverage your platform to create something of value. Value can be subjective, but some examples include shipping a new integration or plugin that increases the usability of your products or integrating your APIs and SDKs into their web or mobile apps to deliver a better experience for their customers.

Posted on

When to Build vs Buy an API Analytics Solution

Purchasing a new enterprise analytics solution can be a great experience if you’ve never purchased software before, yet it can be a daunting task. There can be a variety of analytics vendors with overlapping features for a use case yet each has its strengths and weaknesses. As an alternative to purchasing ready-made SaaS, you can also build your own in-house API analytics infrastructure on top of open-source software like Spark, Druid, and Elasticsearch. This article digs into when it makes sense to build vs buy ready-made analytics solution and provide a point-based framework for evaluating API analytics solutions and perform the proper diligence.

The first decision a company should make is whether they want to build the infrastructure or purchase a ready-made solution. There are benefits and risks to both. In general, purchasing shortens the delivery of a well-polished analytics solution with lower cost in time and money compared to homegrown, but a homegrown gives you greater control over what is tracked and presented.

Posted on

Mastering API Analytics for API Programs: Cohort Retention Analysis

There are few metrics more critical than retention for a platform business. If you’re acquiring customers for $25, but they stop using your API after a month, then you have a leaky boat. Don’t spend more money on developer acquisition until retention is fixed. This requires accurate measurement of API retention.

If you came from a web or mobile product background, you may already be familiar with mobile retention to measure how many acquired users keep using a mobile app. Growing a B2B platform requires tracking similar KPIs to measure the success of your acquisition and product strategies. This article will dig into the best practices for tracking and increasing API retention.

Posted on

13 API Metrics That Every Platform Team Should Be Tracking

A list of the most important API metrics every API product manager and engineer should know, especially when you are looking into API analytics and reporting.

API analytics

Identifying Key API Metrics

Each team needs to track different  KPIs  when it comes to APIs. The API metrics important to infrastructure teams will be different than what API metrics are important to API product or API platform teams. Metrics can also be dependent on where the API is in the product lifecycle.

An API recently launched will focus more on improving design and usage while sacrificing reliability and backward compatibility. A team that maintains an API that’s been widely adopted by enterprise teams may focus more on driving additional feature adoption per account and give precedence to reliability and backward compatibility over design.

You may also like: Analyzing API Call Performance From Different Global Locations Based on cURL Metrics

Posted on

What CDOs and CAOs Struggle With Most

Our team recently attended the Chief Data & Analytics officers (CDAO) conference in Boston and used the opportunity to conduct an informal poll. The conference wills packed with C-suit executives trying to wrangle big data at companies like Tesla, Lionsgate, AMD, Capital One, and Ford. We asked everyone about their analytics challenges. There were two standout issues that we kept hearing about again and again.

1. Their data scientists get bogged down with data access challenges

A recent study showed that data preparation and data engineering tasks represent over 80% of the time consumed in most AI and Machine Learning projects.