- X.509 certificates contain a public key and additional metadata (like an
expiration date that AWS verifies when you upload the certificate). Each
certificate is associated with a private key. When you create a request, you
create a digital signature with your private key and then include that
signature in the request, along with your certificate. AWS verifies that
you're the sender by decrypting the signature with the public key that is in
your certificate. AWS also verifies that the certificate you sent matches
the certificate that you uploaded to AWS.
Use X.509 certificates only when you must sign SOAP-based requests. In all other cases, use access keys.
Vector Databases Usage: Typically used for vector search use cases such as visual, semantic, and multimodal search. More recently, they are paired with generative AI text models for conversational search experiences. Development Process: Begins with building an embedding model designed to encode a corpus (e.g., product images) into vectors. The data import process is referred to as data hydration. Application Development: Application developers utilize the database to search for similar products. This involves encoding a product image and using the vector to query for similar images. k-Nearest Neighbor (k-NN) Indexes: Within the model, k-nearest neighbor (k-NN) indexes facilitate efficient retrieval of vectors. A distance function like cosine is applied to rank results by similarity.
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