When it comes to building reliable and scalable software, few organizations have as much authority and expertise as Google. Their Site Reliability Engineering Handbook, first published in 2016, details their practices to maintain reliability as Google scaled. But when you have over a million servers running thousands of services across more than twenty data centers, how do you monitor them in a consistent, logical, and relevant way?
With the right load balancing in place, the demand of increasing web traffic can become manageable, but how do you determine which load balancing algorithm is best suited for your applications? Does the ease of use of static load balancing better suit the services you provide, or would your system benefit from a more complex and dynamic set of algorithms to maximize efficiency? In this blog post, we discuss what to consider when deciding on the right load-balancing algorithm.
“How much Inventory is left for the next batch of production?” Is this easy for you to answer this? If not, then there is a management glitch, which you must take care of. If your organization is still keeping a track of inventory manually it must be a time and money-consuming task. Whereas, if an organization wishes to switch to an automated Inventory Management Software, it makes the task very easy. Let us first know what inventory is & how inventory management helps!
Rich Costello, Senior Research Analyst at IDC has recently developed an Analyst Brief that looks at the growing need for proactive service quality management and optimization tools for communication and collaboration environments. As the world pivoted online during the COVID-19 pandemic, few companies were ready to support a fully virtual workforce that still required constant connection and to remain as productive as possible.
Houzz is where millions of homeowners and home improvement professionals go to seek inspiration and supplies for their remodeling projects. But to continue as the leading platform for home remodeling and design, the Houzz tech stack needed a renovation of its own as the company scaled. In response, the Houzz team began by revamping their monoliths into microservices.
IT teams in modern workplaces are no longer spending the bulk of their time troubleshooting and break/fixing issues. As in any service industry in the consumer world, IT service workers are now expected to deliver a great experience to their consumers – the employees. Managing the workplace has become much more like managing a theme park, where every aspect of its real estate should exhibit interest, joy, and fun; everything that makes up a great experience.
Legendary race car driver Carroll Smith once said, "until we have established reliability, there is no sense at all in wasting time trying to make the thing go faster." Even though he was referring to cars, the same goes for technology: no amount of code optimization or new features can replace stable systems. Unfortunately, much like race cars, it's hard to know that a system is unreliable until it blows a tire, the brakes stop working, or the steering wheel comes off the column.
This article was originally published in The New Stack and is reposted here with permission. You might need to perform anomaly detection or forecasting if you’re working with time-series data. The first step before working on your time series is finding the right data store. To effectively detect or forecast your data, you will require a data store that can handle a large volume of data at a high ingest rate. Therefore, you might want to look at using a purpose-built time-series database.
It’s already September! Time flies by when you’re getting things done, and we’ve been a busy bunch of bees here at Honeycomb. 🐝 We’re excited that we’ve gotten to share some of those changes with you already, like our relaunched interactive sandbox and the beta release of our OpenTelemetry log support and Go distribution, but that’s just the tip of the iceberg.
