With search, our goals help you find the information you are looking for – quickly and when you need them. While the search has become much more skilled over the years, two things remain holy: speed and reliability. These are simple principles, but they require new and creative solutions to achieve worldwide. Here is an update on how to keep searching quickly and reliably.
Hiding you time with each search
We know you expect searching to provide the information you are looking for faster than a moment. Therefore, delivering results in a fraction of a second is our baseline, and as we improve the search and build new features, it is to remain quick and reduce latency priorities.
When we talk about latency, we measure the time between entering a search and seeing results. As a Pit crew, our teams look at any component of the search to find ways to shave milliseconds. Any increase in latency (from a new feature or change to search) must be offset by making another part of the search faster. This causes teams to continuously optimize phasing of slower code and less used features and improvement of the search.
Trimming time from individual queries adds great time savings for people using search. Overall, for the past two years, these latency time improvements have saved users over 1 million hours every single day.
When we roll out major improvements to search from the knowledge graph to AI listings, we focus on reducing latency. The latency time improvements we have already made with AI summaries have saved users another half a million hours daily.
To keep the search ran around the clock
While the speed is critical, the search must first and foremost be reliable and accessible when you need it. From record high searches during cultural events such as global sports moments to critical searches related to natural disasters, search is built from the bottom of being available to people around the world, around the clock – so you can get the information you need.
Our systems are designed to deal with tremendous demand and operate under pressure, even when faced with unforeseen waves in searches. Search data scientists constantly evaluates subtle signals, such as users who refresh a page, to identify cases where the search does not meet people’s expectations. Engineers then use these signals to identify weaknesses in the system and build upbours to prevent power cuts.
We have also built a first-in-class search infrastructure and have a team dedicated to maintaining it. Our servers are built to process billions of searches every day and connect you with the most useful results from the Internet, regardless of the capacity of your network or device.
An average user must complete about 150,000 queries on Google before encountering a failure due to an error in our search infrastructure. This means that if you searched 10 times a day, it would probably take you more than forty years before you encounter a server-side error.
Our team’s fine -tuning constantly and optimized to ensure that search is the reliable, lightning -fast tool you expect, no matter where you are.